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Case 7 - Engineered vs. Catalogued Made-to-Order
Supply Chains: Pipe Supports used in Power Plants
7.10
Case 7 - Engineered vs. Catalogued Made-to-Order Supply Chains: Pipe Supports
used in Power Plants ................................................................................................................... 1
7.10.1 Business Case ........................................................................................................... 1
7.10.2 Background ................................................................................................................ 1
7.10.2.1 Power Plant Construction ................................................................................... 1
7.10.2.2 Pipe Supports in Power Plants ........................................................................... 2
7.10.2.3 Types of Pipe Supports ...................................................................................... 2
7.10.2.4 Pipe Support Suppliers and Product Standardization ........................................ 3
7.10.2.5 Need for Lead Time Reduction in Pipe Support Supply Chains ........................ 4
7.10.2.6 Methodology for Collecting Case-study Data ..................................................... 5
7.10.3 Characterization of Current Supply-chain Practices .................................................. 6
7.10.3.1 Alternative Supply Chain Configurations ............................................................ 6
7.10.3.2 Description and Analysis of Five SC Configurations and Sixth Alternative ........ 8
7.10.3.3 Selection Among Alternative SC Configurations .............................................. 10
7.10.4 Metrics ..................................................................................................................... 11
7.10.5 Analysis of Various SC Lead Times and Batch Sizes ............................................. 14
7.10.6 Analysis of Value-added Time over Total Delivery Lead Time ................................ 15
7.10.6.1 Value Stream Map ............................................................................................ 15
7.10.6.2 Value-stream Analysis Results ......................................................................... 16
7.10.6.3 Causes of Non-value-added Time .................................................................... 17
7.10.7 Detailed Value Stream Map for Fabrication ............................................................. 18
7.10.8 Process Simulation Showing Impact of Contributors to Lead Time ........................ 19
7.10.8.1 Value of Using Simulation ................................................................................ 19
7.10.8.2 Simulation of Design Process for Pipe Supports .............................................. 20
7.10.8.3 Design Process Model in STROBOSCOPE ..................................................... 21
7.10.8.4 Implementation and Simulation of Supply Chain Tasks ................................... 23
7.10.8.5 Scenario 1: Deterministic Model with Batching ................................................ 23
7.10.8.6 Scenario 2: Probabilistic Model with Batching, Variability, and Multitasking .... 25
7.10.8.7 Summary of Simulation Findings ...................................................................... 29
7.10.9 Supply Chain Improvements .................................................................................... 30
7.10.9.1 SC Improvements Implemented to Date .......................................................... 30
7.10.9.2 On-going Improvement Efforts ......................................................................... 32
7.10.10
Conclusions .......................................................................................................... 34
7.10.10.1 Case Study Conclusions ................................................................................. 34
7.10.10.2 Improvement Areas worth Further Investigation ............................................. 34
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7.10 Case 7 - Engineered vs. Catalogued Made-to-Order Supply
Chains: Pipe Supports used in Power Plants
7.10.1 Business Case
Many construction inefficiencies are due to supply chain (SC) problems that occur at the
interface between processes, disciplines, or organizations (Vrijhoef and Koskela 2000).
This case study illustrates such problems in the supply of pipe supports used in power
plants. The key business issue is that pipe supports often arrive late at the construction
site, even though-relatively speaking the majority of supports are straightforward to
engineer and inexpensive to procure. The need therefore exists to reduce the lead time for
designing, procuring, fabricating, and shipping pipe supports in order to avoid late
arrivals at the site. This can be done by using the capabilities available by all SC
participants.
7.10.2 Background
7.10.2.1
Power Plant Construction
Power plant construction has experienced an unexpected boom in recent years. “Between
1999 and 2001, about 83,000 MW of new capacity has come on line in the U.S., adding
nearly 10% to the generation base” (ENR 2001). Real and perceived needs for new power
have resulted in strenuous demand being put on the order-to-delivery time of power
plants, so that today’s projects have to be executed not in a fast-track, but in a ‘flashtrack’ mode (ENR 1997).
Power plant projects are complex and require thousands of components, including
major mechanical and electrical equipment, vessels, structural steel, pipe, pipe supports,
instrumentation, valves, fittings, and so on. SCs managed to make individual and sets of
components flow, but also coordinated so that they will come together and match where
and when needed, are a ‘must’ for project success. For each power plant component, SC
participants not only affect the effectiveness and efficiency of the corresponding SC(s),
they could also introduce a variety of inefficiencies. Inefficiencies need to be identified
and eliminated to better satisfy not only customer, but all SC participant needs as well as
to achieve project goals, otherwise, they will impact project completion.
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Pipe Supports in Power Plants
Power plants are configurations of a fuel storage and combustion system; a foundation
system; a structural system; a power-generation-, power-conversion-, and transmission
system; and various piping systems. They include piping systems for high- and lowpressure steam, feed-water, hot and cold reheat, and other systems such as condensate
and heat recovery steam generator systems (HRSG). In turn, these systems include pipe
as well as pipe supports, valves, in-line instrumentation, etc.
A pipe support is as an assembly of components that attaches to the pipe and transfers
the pipe’s load to the building or another structure in a manner that will prevent excessive
movement under static and dynamic conditions during plant startup, operation, and
shutdown. Therefore, pipe supports represent the interface between the building and other
structural systems and the various piping systems, which interact with the location of
equipment and vessels in the plant.
7.10.2.3
Types of Pipe Supports
Examples of pipe supports are ‘constants’ (labeled ‘A’ in Figure 1) and ‘variable springs’
(B), ‘dynamic supports’ (or ‘snubbers’) (D), ‘slide bearings’ (F), ‘isolated supports’ (G,
H), and ‘pipe shoes’ (pieces of pipe that transfer gravity loads to a structure underneath
the pipe).
C
C
C
C
C
G
B
B
A
B
E
C
B
A
I
C
E
D
G
C
C
C
C
H
F
C
C
B
D
C
H
D
A
H
Figure 1: Example Pipe Supports (from Pipe Supports Limited Inc.
http://www.pipesupports.com visited on 02/26/02)
A pipe support has three main parts: (1) the device which itself is also called a ‘pipe
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support’, (2) the attachments (labeled ‘E’ in Figure 1) used to connect the pipe support
device with the building structural system, and (3) the complementary hardware (‘C’ =
pipe clamps and ancillary equipment; ‘I’ = turnbuckle) that connects the pipe support
device with the steel attachment.
7.10.2.4
Pipe Support Suppliers and Product Standardization
Suppliers of pipe supports offer a large variety of products, ranging from the supports
they commonly advertise in company-specific catalogs (e.g., catalogs from Piping
Technology and Products Inc., Lisega, AAA Technology and Specialist Co., Anvil
International Inc., Shaw, etc.) to custom designs. To our knowledge, pipe support
suppliers can fabricate in their job shops more-or-less anything the customer wants,
especially if the business deal is right. On occasion, fabricators will nevertheless refer a
customer to a competing supplier for exceptional specialty supports for which the
customer can get a better deal than the supplier’s resale. A limited extent of business
diversification stems from some companies focusing on supplying to the petrochemical
industry and others to the power plant industry; others focus on specialty supports such as
those needed to suit cryogenic conditions. Even so, cyclic markets force many companies
to serve several industries.
Pipe supports from Grinnell (now part of Anvil International Inc.) have de-facto
served as a domestic industry standard because this company has been around for the
longest time and, early on, on its own worked toward defining a comprehensive set of
supports. Companies such as AAA allude by their advertizing to the equivalence of their
products to Grinnell’s in ‘or equal’ procurement specifications.
Despite the fact that companies know which of their products can substitute for a
competitor’s, no industry-wide standard for pipe supports in their multitude of project
applications presently exists, neither in the US nor internationally. The petrochemical
sector of the industrial construction industry appears to be furthest along in terms of
standardization whereas the power plant sector appears to lag behind in this regard, but
further research is in order to determine what has driven and enabled these different
sectors to move at different speeds towards industry-wide product standardization.
Support suppliers compete in the domestic and overseas market by offering different
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products and services. One example is an overseas supplier who offers supports, more
compact than those otherwise available in the US, that are favored especially in cases
when plant congestion is an issue. Another example is a domestic supplier who by default
galvanizes all hangers, unless the customer insists on having them painted; other supports
are galvanized only if customers request it. A galvanized finish is known to have a higher
life-cycle value than a painted finish, but galvanization tends generally to be more
expensive and adds to the delivery lead time. Given this company’s specific geographic
location and the presence of multiple galvanizers nearby, these costs are not exorbitant.
This company benefits overall in that it can reduce its SCM effort, thanks to the product
simplification achieved by standardizing on a higher quality finish, while delivering
greater value at a marginal if any extra cost at all to its customers. Based on life cycle
analysis, this cost would be offset.
From a SC performance perspective, a wealth of product variety is a mixed blessing.
Engineering firms value the freedom of being able to design what they consider to be the
best solution given the project requirements and then procure what they design, but
focusing on product design alone does not automatically result in a good delivery
process. If each and every product to be supplied to a project is unique, then managing
the SC is significantly more complex than it would be if products were more standardized
and supplied to a project in multiples. Custom engineering of a product may be a ‘penny
wise and pound foolish’ proposition when the SC is not designed to accommodate it. The
movement towards ‘mass customization’ aims to trade off such product- against process
performance choices.
7.10.2.5
Need for Lead Time Reduction in Pipe Support Supply Chains
Relatively speaking, most pipe supports are inexpensive and require straightforward
engineering when compared to the cost and amount of engineering going into other
power plant systems. Up to about 20% of the total number of supports in a power plant
are customized. Nevertheless, problems in supplying pipe supports of any kind can
compromise the success of the overall project. The reality is that a piping system is not
complete and ready for start-up testing and turnover unless all pipe supports are in place.
The problem may start early on in the delivery process. Pipe support design requires
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input regarding the plant requirements and load conditions; the design of the structural
steel system; the location of mechanical equipment, vessels, and instrumentation; as well
as the physical (e.g., diameter, material, routing) and system characteristics (e.g.,
operating temperature and pressure) of the pipe that connects them. Current practice often
is to define these inputs first and to push pipe support design towards the end of the
power plant design process. Since power plants nowadays are managed as fast-track or
even flash-track projects, design and construction overlap. When support design gets
done in a rush and at the last minute, the downstream SC may get strained. For example,
failing to allow sufficient lead time to fabricate and supply pipe supports to the site, or
failing to coordinate the delivery of supports with the delivery of pipe and other system
components, can make it necessary for field workers to use temporary supports (e.g.,
chainfalls) so that they can make progress on pipe installation and circumvent erection
delay, but such practices create later out of sequence rework in the field, affect on-site
piping productivity, and ultimately may result in project delays and budget overruns.
7.10.2.6
Methodology for Collecting Case-study Data
This case study was initiated with the support of Parsons E&C one company <confirm
with Frank that it is OK to name his company>who is a team participant member in
PT172, and others expressing an interest in it. Data regarding industry practices at large
however, was collected by means of an extensive literature review and interviews
conducted with tens of practitioners working for a range of engineer-procure-construct
(EPC) firms and pipe support suppliers. The resulting findings therefore do not represent
practices at any one company, instead, they characterize industry practices in a more
general way.
The literature and interface with other researchers and practitioners in the power
plant industry, including several with a CII research track record and others who have
been involved in developing PIP, failed to reveal any research specifically focused on the
design, delivery, or installation of pipe supports. This is striking, especially given the
number of studies conducted to date on piping and related productivity, and common
complaints about late deliveries.
The data presented in this study was obtained from various firms and pieced together
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as needed because the scope of the SC in this case spans multiple organizational
boundaries. The research findings therefore do not represent any one specific project,
though they are indicative of current practices in the power plant construction industry.
The researchers would like to challenge individual companies and their SC partners to
consider the presented analysis and conclusions as a basis for repeating the research
process using their own process and project data in order to confirm the orders of
magnitude of the metrics and develop an appreciation for the research findings and SC
opportunities presented here.
7.10.3 Characterization of Current Supply-chain Practices
7.10.3.1
Alternative Supply Chain Configurations
To characterize the SC for the delivery of pipe supports, five alternative configurations
have been captured in distinct cross-functional maps. Each map shows the activities
performed in engineering, procurement, and fabrication. The main participants in the SC
for pipe supports are (1) engineering firms, (2) pipe support suppliers (who detail and
fabricate the supports), and (3) contractors. Pipe fabricators may play a role in this SC but
they are not necessarily involved. Engineering (1) and contracting (3) may lie within the
scope of work of a single EPC firm. Delivery to site and construction were not detailed in
this case study. (Meaning intent not clear in last sentence).
The five alternatives require more-or-less the same activities to design and fabricate
the supports. Different SC participants, according to their business interests,
competencies, and capacity, may take responsibility of the design and/or detailing of pipe
supports in order to suit different project requirements. The configurations are:
Configuration 1 (Figure 2): Engineering firm designs the pipe supports. Supplier
details, fabricates, and supplies the supports. Contractor installs. This model
describes, by far, the most common practice in the industry.
Configuration 2 (Figure 3): Engineering firm routes pipe and performs pipe
stress analysis. Supplier designs, details, fabricates, and supplies the supports.
Contractor installs.
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Configuration 3 (Figure 4): Supplier fully designs pipe supports. Contractor
installs.
Configuration 4 (Figure 5): Contractor takes responsibility for pipe-support
design and fabrication, though likely will subcontract this work out, and then
installs.
Configuration 5 (Figure 6): Pipe Fabricator takes responsibility for pipe-support
design and fabrication. Contractor installs.
Figures 2 through 6 show abridged versions of these five supply chain configurations.
Detailed versions are presented in Arbulu (2002) and Tommelein and Arbulu (2002).
Route Pipe
LocatePipe
Supports
Perform
Pipe Stress
Analysis
Design Pipe
Support
Chec k
Interference
and Loads
Select
Supplier &
Send Info
Approve
Analyze
Information
Negotiate
Engineering Firm
Fabricate
Pipe Supports
Deliver Pipe
Support
Pipe Support Supplier
Matc h Pipe
and Supports
Ins tall
Supports
Contractor
Figure 2: Configuration 1 - Engineering Firm Designs and Supplier Details, Fabricates,
and Supplies Pipe Supports used in Power Plants
Route Pipe
Locate Pipe
Supports
Perform
Pipe Stress
Analysis
Select Supplier
Check
Interference
and Loads
Send
Inform ation to
Supplier
Approve
Analyze
Inform ation
Negotiate
Engineering Firm
Design Pipe
Support
Fabricate
Pipe Supports
Deliver Pipe
Support
Pipe Support Supplier
Match Pipe
and Supports
Install
Supports
Contractor
Figure 3: Configuration 2 - Engineering Firm Routes Pipes and Performs Pipe Stress
Analysis. Supplier Designs, Details, Fabricates, and Supplies the Supports
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Select
Supplier &
Send Info
Route Pipe
Check
Interference
and Loads
Approve
Budget
Design Pipe
Support
Negotiate
Engineering Firm
Analyze
Inform ation
Locate Pipe
Supports
Perform
Pipe Stress
Analysis
Fabricate
Pipe Supports
Deliver Pipe
Support
Pipe Support Supplier
Match Pipe
and Supports
Install
Supports
Contractor
Figure 4: Configuration 3 - Supplier Fully Designs Pipe Supports
Route Pipe
Locate Pipe
Supports
Perform
Pipe Stress
Analysis
Send
Inform ation to
Contractor
Engineering Firm
Fabricate
Pipe Supports
Deliver Pipe
Support
Buy from
Supplier
Match Pipe
and Supports
Pipe Support Supplier
Analyze
Inform ation
Design Pipe
Support
Install
Supports
Contractor
Figure 5: Configuration 4 - Contractor Takes Responsibility for Pipe-support Design
and Fabrication
Route Pipe
Locate Pipe
Supports
Perform
Pipe Stress
Analysis
Send
Inform ation to
Pipe
Fabricator
Engineering Firm
Fabricate
Pipe Supports
Deliver Pipe
Support
Pipe Support Supplier
Analyze
Inform ation
Des ign Pipe
Support
Buy from
Supplier
Pipe Fabricator
Match Pipe
and Supports
Install
Supports
Contractor
Figure 6: Configuration 5 - Pipe Fabricator Takes Responsibility for Pipe-support
Design and Fabrication
7.10.3.2
Description and Analysis of Five SC Configurations and Sixth
Alternative
Configurations 1 through 5: Configuration 1 is most commonly used today for pipe
support delivery. This is a ‘cascading’ configuration with more-or-less sequential
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handoffs between organizations. The resultant cascading effect is an important
characteristic in that it allows the information to flow throughout the SC activities with a
low level of interdependency. Less interdependence between participants typically means
better flow of information, although the flow may get stretched out and otherwise
impeded.
By contrast, configuration 2 shows greater reciprocal dependence between the
engineering firm and the support supplier who is in charge of all pipe support design.
Reciprocal dependence allows for greater concurrency and less rework but requires
collaboration to be successful. Sometimes, engineering firms do not have sufficient inhouse capacity to engage in support design and therefore hire the supplier to provide this
service.
Similarly, configuration 3 shows reciprocal dependence between the engineering firm
and the supplier, but here, the information exchange requirements are even greater than
they are in configuration 2, because pipe stress analysis is more involved. Pipe stress
analysis is a service offered by some support suppliers, but engineering firms appear to
favor doing this work in-house for a variety of reasons, including respective system
operation characteristics and plant performance issues
Configurations 4 and 5 also cascade, but the contractor or the pipe fabricator,
respectively, rather than the support supplier, receives the handoff from the engineering
firm. These configurations have been used in practice for small supports where no
significant engineering is required, based on the assumption that pipe fabricators do not
have the skills necessary to design and fabricate supports.
Configuration 6: A sixth configuration that reflects vertical integration between the
engineering firm, the pipe support supplier, and the pipe fabricator has been identified but
was not studied in detail. The Shaw Group (Shaw), initially known for fabrication of
pipe, then for fabrication of pipe supports, and more recently in the news for its
acquisition of Stone and Webster Engineering in 2000, represents this new configuration.
Vertical integration across so many tiers of the SC to yield a single company enabling
Shaw to compete heads-on with many of its own customers, which are EPC firms.
Shaw has become a SC integrator by putting equity into firms that originally were
upstream and downstream from their initial core, pipe fabrication business. They also
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have invested heavily in IT and other technologies (e.g., pipe bending to replace costly
welding operations) to expand the range as well as the product and process quality of
their capabilities. Shaw experienced that gross profit margins in engineering and
construction are lower than those in other parts of its business, but it also is “changing the
status quo of running EPC businesses by conceding that engineering is a commodity and
that engineering services must be sold with a value-added component” (ENR 2002). An
integrated SC package appears to appeal to a variety of customers in the market for
power today.
7.10.3.3
Selection Among Alternative SC Configurations
The selection among alternative SC configurations to best suit any one project must take
into account numerous factors, including the capabilities (e.g., core and non-core
competencies), capacity, and strategic corporate goals of the companies involved, as well
as industry trends and the current and forecast market situation. In practice, engineering
firms may use more than one SC configuration to balance the needs of several,
concurrent and prospective projects. For example, on one project, the engineering firm
may select a supplier early and collaborate with them using configuration 2 for the
engineered-to-order supports, then involve that supplier using configuration 1 for all
remaining supports that simply can be selected from that supplier’s catalog and made to
order.
The selection of a SC configuration for pipe supports may be governed by decisions
the power plant owner makes. In part due to the rapid growth of the power plant industry
during the last few years and, accordingly, the number of projects individual owners
wanted to initiate within a short time span, some owners have established direct alliances
or long-term agreements with major equipment suppliers (also see the “Transformer”
case in this research report) but also with pipe fabricators and even with pipe support
suppliers.
In order to improve their own business performance, EPC firms have also established
alliances with support suppliers. For example, Electronic Data Interchange (EDI)
initiatives have been implemented in order to ease and expedite the interfacing between
processes. EDI initiatives represent a good foundation to support increasing levels of
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standardization of products and processes as well as power plant modularization
initiatives.
To achieve the best results in terms of value (including cost, quality, delivery lead
time, product standardization, etc.), the owner makes decisions about whether or not its
supplier alliance or an EPC firm’s alliance offers the best solution for each particular
power plant project.
7.10.4 Metrics
To complement the SC maps, several metrics were selected to gauge performance in
different supply chain phases as well as in the SC at large. Some data for metrics was
readily available whereas other data was more difficult to obtain from practitioners’
current project management systems. Examples of metrics are the following:
Lead time: Lead time may refer to the entire time elapsed from order to plant start-up, or
more specifically to, e.g., the time needed to approve detailed drawings prior to the start
of fabrication, the time to fabricate a support, the time to deliver supports to the site,
staging time on site (arrival of supports prior to their installation), etc.
Supply-chain lead time depends on various factors, many of which pertain to the
complexity of a product and variety in a product line. Supply-chain lead time is the sum
of five elements: (1) direct work or processing time, (2) inspection time, (3) wait time, (4)
move time, and (5) decision-making time. Decision-making time may be critical
especially when several participants interact, playing different roles for different
organizations. Information processing may get delayed for days or even weeks, thereby
holding up other SC steps.
The lead time of a single SC is of relative importance when compared to the overall
project delivery process. In order to cope with project complexity, project managers often
rely on the 80/20 rule-of-thumb: focus on the 20% of the activities, components, or the
like, that contribute to 80% of the cost, delays, or other problems. Using this rule,
however, pipe supports seldom make it to their list of priorities. Pipe supports are not
typically ‘critical’ or ‘pacing’ items in a schedule as for instance turbine-generators or
transformers are. According to this kind of thinking, also reflected in the PEpC study (CII
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PT-130 ref), pipe supports on the critical path would be a scheduling anomaly.
Now consider the 80/20 rule after it has been successfully applied. The 20% has been
managed so as to no longer be a problem. The criticality therefore shifts to one or several
items that previously were in the 80% list. Management must therefore be flexible and
redirect its attention as the project gets executed in order to recognize and deal with these
shifts. This presents an example scenario when pipe supports are critical. In CPM
scheduling, this phenomenon is well known. As a schedule increasingly gets compressed,
more parallel paths in the network become critical (also see Goldratt’s “The Goal” that
describes how bottlenecks shift in a production setting). Project managers on flash track
projects therefore have more to manage than managers on more slowly paced projects
had to.
Lead time also is of absolute importance. Overall benefits of lead time compression
are: (1) faster delivery of the product or service to the customer, (2) reduced need to
accurately forecast future demand, (3) less opportunity for disruption in the SC due to
(design) changes, (4) greater possibility that participants will interact in a timely fashion
with other SC participants, (5) easier synchronization of one SC with others (e.g.,
merging supply chains at the site), and (6) less opportunity for products to become
obsolete. It is possible to directly attack the most visible waste just by flowcharting the
process, then pinpointing and measuring non-value-added activities (Koskela 1992). This
brings us to the next metric.
Value: SCM aims to deliver value to the end customer. Accordingly, all SC activities
must be assessed in terms of what value they bring to a customer. This is not easy to do!
Direct work time (as distinct from contributory work time and wasted time) may be used
as a token for value, though this hides inefficiencies in process execution due to poor
work methods design and in the allocation of work to those who could get it done in the
best way (work structuring).
After determining value vs. non-value adding activities, a lean transformation process
will seek to eliminate all waste from the activities and operations with handoffs between
them that are executed to bring that product (or service) to market. This set of activities,
operations, and associated information make up the value stream. A value stream
perspective should look across individual activities, functions, departments, and
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organizations, and focus on system efficiency rather than local efficiency within any one
of these.
Value streams are mapped and analyzed using a tool known as Value Stream
Mapping (VSM). VSM was created by practitioners at Toyota as a tool to “make
sustainable progress in the war against muda” (‘muda’ is the Japanese word for ‘waste’)
(Rother and Shook 1998). It helps to effectively design a lean production system. VSM
includes creating a map of the flow of material as needed to make a family of products
through their production steps, and the flow of information from the customer back to
each production process. A current-state map of in-plant value streams then serves as the
basis for developing future-state maps that leave out wasted steps while pulling resources
through the system and smoothing flow. The difference between the current state and
potential future states provides a road map to start the implementation of performance
improvements.
The scope of many VSMs has been restricted to remain within the boundaries of a
single organization. Recent efforts (e.g., Jones and Womack 2002) apply VSM on a
macro scale, considering supply-chain upstream and downstream of a specific
organization. Adopting such a view is most appropriate in the highly fragmented AEC
industry.
One value-based metric is the actual work time vs. the total time a products spends in
a system, also known as value added time over lead time. An application and analysis of
this metric in the SC of pipe supports is presented in sections 7.10.6 and 7.10.7.
Batch size: Batch size refers to the unit of handoff of information or work from one SC
participant to the next. An analysis of the impact of batch sizing on SC performance is
presented in section 7.10.5. Section 7.10.8 then describes different computer-based
simulation models based on the SC of pipe supports to illustrate the effects of batching,
multitasking, and variability as contributors to lead time.
Cost: Besides time, value, and quality, cost is an important metric. However, cost data is
more sensitive to obtain and the researchers did not insist on doing so.
Other considerations in comparing different SC configurations may include, to name but
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a few: the distance or directness of control and communication between the various SC
participants and the number of process steps in the SC (length of the SC).
7.10.5 Analysis of Various SC Lead Times and Batch Sizes
To illustrate the use of various lead time metrics, data was analysed on 680 pipe hangers
and supports from one power plant currently under construction. In this case, the SC of
pipe supports followed the structure of SC configuration 1 (engineering firm designs pipe
supports).
Figure 7 represents several lead times for different SC activities and handoffs, starting
with the date at which the first purchase order was issued and ending with the actual
shipment date to the site. For example, the handoff between design and fabrication is
represented by the number of calendar days since the engineering firm issued the
drawings to the supplier (‘Issued’) until the support supplier sent detail drawings for
approval (‘SA’). This handoff took more than 8 weeks on average (61 days = 8.7 weeks),
whereas the fabrication process itself took no more than 6 weeks (27 days + 13 days). To
the extent it could be determined, this particular handoff took so long because of the
interdependence between participants in the SC and the high degree of analysis and
verification required after each handoff, in part due to lack of product and process
standardization.
Issued
SA
61d
18d
18d
RF
- 'Issued' ref ers to the date when the engineering f irm issued the
drawings to the supplier.
- 'SA' ref ers to the date at which the supplier sent in shop drawings to
the engineering f irm.
- 'RF' ref ers to the date at which supports were ready f or f abrication.
- '1st Ship' ref ers to the shipping date originally promised by the
supplier.
- 'Schedule Ship'is the scheduled shipping date, a date af ter the f irst
ship date if the supplier missed their earlier promise.
- 'Act. Ship' ref ers to the date that supports were actually shipped to
the site.
- 'Site Need Date'is the date obtained f rom construction to support
their original plan.
8d
10d
8d
1st Ship
27d
13d
13d
Sched. Ship
19d
15d
19d
Act. Ship
6d
2d
6d
Site Need Date
32d
Legend
d=calendar day s
Mean
Dev . Standard
Average Pipe Support Delay
Figure 7: Lead Times in Pipe Support Detailing, Fabrication, and Delivery
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7.10.6 Analysis of Value-added Time over Total Delivery Lead Time
7.10.6.1
Value Stream Map
Using VSM, the flow of work was documented throughout the design, procurement,
detailing, and fabrication phases of pipe supports based on SC configuration 1, which is
most commonly used by practitioners in the power plant industry today (Figure 2). The
presented value stream analysis did not consider the installation of pipe supports on site
because we were unable to get real project data to support the case study. Based on
configuration 1, we analyzed the value stream for the supply chain as a whole (this
Section) and then detailed the fabrication phase (section 7.10.7).
The analysis presented here focuses on the evaluation of value added and non-valueadded times. The results are complemented with observations about the execution of the
SC activities and the behavior of the SC participants that possibly cause waste along the
chain.
Figure 8 depicts the value stream each single pipe support follows from design to
delivery to the site. Note how different this map is, with its focus on the flow of a single
support, as compared to, for instance, a project-based CPM schedule! This VSM shows a
series of linked activity boxes with triangles in between. In terms of duration, activity
boxes represent the time a pipe support will be in process in a conversion activity. This
time gives an upper-bound estimate of value-added time. The triangles represent the time
a pipe support waits until it gets processed by the next activity. This waiting time may
different causes that will be explained in Section 7.10.6.3 and 7.10.8 in this report.
Triangles do not have any specific duration. Instead the VSM shows total durations
between activities (arrows at the top of the activities). Accordingly, the difference
between the total time in the system (sum of times shown on arrows) and the processing
time (sum of times shown under each activity box) represents a lower bound on the total
non-value-added time or waste.
The value-added times were determined using two sources of information: factual
data from a specific power plant project and more anecdotal data obtained by
interviewing tens of piping engineers and pipe support designers from engineering firms
as well as support suppliers.
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The unit of value-added time is ‘man-hour.’ Since more than one person may
contribute to the completion of any one activity, the real time needed to perform an
activity may differ from the value-added time shown, in function of the resource
allocation. The total time in the system needs to be understood as the time that a pipe
support takes to flow through the SC from start to end. The unit of time in the system is a
week, considering that each week corresponds to 40 hours of work per person.
8 weeks
Route Pipe
2-2.5 m -hrs
2- 3 weeks
2- 3 weeks
Loc ate
Pi pe
Supports
Analyze
Pi pe
Stres s
Des ign
Pi pe
Support
Chec k
Loads and
Interferenc e
0.5 m-hrs
1.8-2.3 m-hrs
0.5-1.0 m-hrs
3.5 m-hrs
2 weeks
1 week
Reinforc e
Struc ture
(inc . New
Details )
Prepare
Pi pe
Support
Drawings
Selec t
Suppli er
and
Send Info
Analyze
Info from
Eng. Firm
Agree on
Pric e
(Inc .
Budget)
3.5- 6 m-hrs
1m -hrs
1- 2 m -hrs
0.4- 0.6 m-hrs
0.1- 0.5 m-hrs
2- 4 weeks
1- 3 weeks
6- 8 weeks
Is s ue Pipe
Support
Details for
Fab
Approve
Drawings
Fabric ate
2-5 m-hrs
1-2 m-hrs
24 m-hrs
1- 2 weeks
2 weeks
1 week
Supports
Ready to
Ship
Deliver
Supports
On Site
T otal Duration
= 28 -37 weeks
Hours per week
= 40 hrs .
T otal T ime in Sys tem = 1120 - 1480 hrs
1 m -hrs
Duration
(hrs)
Notes:
1.
2.
-
All durations are per uni t of s upport (m-hrs = man hours ).
Underlined values have been as s um ed by res earc hers .
T he num ber of m an-hours for the ac tivity "Agree on P ric e" was as s um ed as 0.1-0.5 m -hrs /s upport.
T he num ber of m an-hours for the ac tivity "Fabric ate" was as s umed as 24 m-hrs /s upport.
T he num ber of m an-hours for the ac tivity "Del iver" was as s um ed as 1 m-hrs /s upport.
In all c as es , the queue times are s o big than thes e as s umpti ons won't affec t the final res ults .
The Supplier performs the Activity
T otal Queue T ime
= 1078-1428
T otal P roc es s ing T ime =
T otal T ime in Sys tem
42-52
= 1120-1480
%
96 - 96.5%
4 - 3.5%
100%
Interaction between Engineering Firm and Supplier to perform the Activity
The Engineering Firm performs the Activity
Figure 8: Value Stream Map - Supply Chain of Pipe Supports
7.10.6.2
Value-stream Analysis Results
Analysis of this VSM shows that a pipe support takes a total duration ranging from 28 to
37 weeks to flow through the system. One reason for this variation is the diversity and
complexity of supports that are covered by the design, detailing, and fabrication phases as
shown in Figure 8. The analysis shows that only about 4% of the total time a pipe support
needs to flow through the system represents value-added time. This means that only
about 1.6 hours out of a 40-hour work week really add value to the final pipe support
product. The remaining 96% of the time or 38.4 hours out of a 40-hour work week
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represent non-value-added time.
7.10.6.3
Causes of Non-value-added Time
Causes of waste in this particular supply chain are mainly related to the time resources
(information and materials) wait to be processed and the amount of rework in the system.
Wait time in part stems from batching practices. Batching is an important consideration
in supply chain performance assessment because bigger batch sizes cause longer waiting
times and therefore longer lead times.
This case study identified several types of batches with different sizes along the
supply chain. Figure 9 depicts two of these, namely (1) the release of design information
from the engineering firm to the support supplier, and (2) the shipment of completed
supports from the support supplier to the site. As shown, some batch sizes on this project
were as big as 260 supports. This means that the first support had to ‘wait’ for the other
259 supports to be processed, until all were released to the next activity.
280
260
240
Batch Size
Delivery of Supports to the Site
Release Design Info to Supplier
220
200
180
160
140
120
100
80
60
40
Days
20
0
0
10
20
30
40
50
60
70
80
90
100
110
120
130
140
150
160
Figure 9: Example of Batch Size Variation
Other contributors to wait time are multitasking practices. In reality, piping engineers and
designers, often aided but also impeded in some way by the tools they need to perform
design activities (e.g., programs require particular sets of input data and won’t run with
data missing), multitask between two or more design processes that may belong to one or
more power plant projects. They do so because not all information or other resources
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needed to complete a task may be available when they have the time to work on that task.
Multitasking enables them to reduce their own idleness, though it does not necessarily
increase their efficiency because each switch of tasks comes at a setup cost.
Unfortunately, more multitasking means that any one task has a smaller likelihood of
being worked on and completed and, consequently, it has to wait longer and its lead time
increases.
Management controls multitasking practices by setting execution priorities. Tasks
with a higher execution priority are ‘expedited’ at the expense of those with a lower
execution priority, which then have to wait longer and get stretched in lead time.
Finally, rework is due to uncertain data being incorporated in the early design phase
of pipe supports or other supply chain phases. Rework may be due to several factors but
especially rework due to errors should not be tolerated as it reduces throughput, the time
to make (design, procure, fabricate, and deliver) a pipe support, and it causes unreliable
workflow. A major rework factor is working from vendors preliminary information, only
to find that connection locations, sizing and ____________have changed.
7.10.7
Detailed Value Stream Map for Fabrication
In Learning to See, Rother and Shook (1996) provide a step-by-step process to analyze
not only the production flow but they also emphasize lean tools to support the workflow
along the different workstations. We have mapped the fabrication of engineered pipe
supports but still lack information to provide a detailed map like theirs for any one
specific product family. Instead, the fabrication process as studied here focuses on the
analysis of value-added and non-value-added times.
Figure 10 depicts a VSM for the fabrication of pipe supports. The fabrication lead
time quoted to us by practitioners varies from 2 to 6 weeks. One reason for this variation
is, again, the diversity and complexity of supports. The number of man-hours per week,
considering a three-shift operation, is 7 days/week * 24 hours/day, which equals 168. The
total number of hours that a support remains in the system until it is delivered to the site
thus varies from 336 to 1,008. In Figure 10, value-added times are shown under each
activity box: the total value-added time is equal to 107.38 hours. This represents between
11% and 32% of the total time that a pipe support remains in the system and it means that
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only 1-to-3 out of 10 hours of work in the fabrication shop really add value to the final
pipe support product.
Cut
Roll/Bend
Drill
Fitup
Weld
2.5 m-hrs
0.33 m-hrs
1 m-hr
40 m-hrs
40 m-hrs
Start Fab
Total Duration
= 2 - 6 weeks
Hours per week
= 168 hrs.
Total Time in System = 336 - 1008 hrs
Durations 1
(hrs)
%
231 - 901
69 - 89%
Total Processing Time =
105 - 107
31 - 11%
Total Time in System
336 -1008
Total Queue Time
=
=
100%
Pack
Final
Inspection
Paint or
Galvanize
2-4 m-hrs
0.5 m-hrs
1 m-hr
The Supplier performs the Activity
Specialty Contractor may perform the activity.
Assemble
and Paint
18 m-hrs
2
Notes:
1. All durations are per unit of support (m-hrs = man hours).
2. Some suppliers use to paint and galvanize the support as part of their standards but in most cases painting is commonly performed in-house. The galvanizing
process is more complicated and usually pipe supports need to be transported to another facility to be galvanized. Specialty contractors perform galvanizing.
Figure 10: Value Stream Map - Fabrication Phase of Pipe Supports
Note that the durations shown in Figure 10 do not exactly match those shown in Figure 8.
The reason is that data was obtained through several interviews with practitioners and
each interviewee has developed a mental model of the SC based on their own experience.
7.10.8 Process Simulation Showing Impact of Contributors to Lead Time
7.10.8.1
Value of Using Simulation
Computer-based process simulation is used next to highlight several contributors to long
lead times, relative to the modest amount of value-added time that is needed to execute
each value-adding activity in the SC for the delivery of capital projects. Contributors to
long lead times are worthy of study because they indicate opportunities for process
improvement. The contributors discussed here tend not to be recognized in traditional
project management practice. Traditional project management relies on mostly
deterministic- rather than stochastic models (such as models that acknowledge an
activity’s duration may not be precisely know, but instead could fall within a range of
values) that further extend in scope to include handoffs and flows, and the delivery of
value. Simulation, then, helps project managers to quantify waste in current practices and
assess opportunities for schedule compression.
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Simulation illustrates dynamically how uncertainty, multitasking, and batching
throughout various SC phases hamper overall SC performance. Uncertainty is introduced
to mimic variability in the system. Multitasking means that a resource is to perform more
than one task and (often randomly) alternates working on one or the other(s). Batching
means that activity outputs are released to the next activity in groups that follow certain
grouping criteria. Individually and in combination, uncertainty, multitasking, and
batching all cause an increase in SC lead time.
7.10.8.2
Simulation of Design Process for Pipe Supports
The aim of the simulation models that are described next is to illustrate how interfaces
between SC tasks affect overall system performance, though not to detail any specific
value-adding task(s) in the SC. The models accordingly cover only an excerpt (Figure 11)
of the process model previously shown in Figure 8. The model could easily be extended
to span the entire process presented in Figure 8, but this was not done in order to keep the
discussion of modeling outputs straightforward.
The excerpt focuses on routing pipe, locating pipe supports, and conducting a pipe
stress analysis. It reflects data collected on several power plant projects. Each of the
tasks, respectively, takes about 2-to-2.5 manhours (mh), 0.5 mh, and 1.8-to-2.3 mh, or a
total of 4.3-to-5.3 mh of value-added time for each support to be designed. However,
practitioners say that a lead time on the order of 8 weeks for a support to go through this
sequence of design steps is required. The presented simulation models provide a rationale
for the causes of this discrepancy, which are essentially related to task variability,
multitasking, and batching. Other factors beyond these may also contribute to this
discrepancy though they are not included in the discussion.
8 weeks
Route
Pipe
Locate
Pipe
Supports
Analyze
Pipe
Stress
2-2.5 m-hrs
0.5 m-hrs
1.8-2.3 m-hrs
Figure 11: Excerpt of Value Stream Map for Design of Pipe and Pipe Supports
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Design Process Model in STROBOSCOPE
The simulation models in this report build on the STROBOSCOPE discrete-event
simulation engine (Martinez 1996) and illustrate several scenarios that combine different
uncertainty levels, different degrees of resource sharing, as well as different batch sizes.
Table 1 summarizes the functionality of the symbols used in these models. All models
were run using STROBOSCOPE (version 1,2,2,0) on a Pentium 566-Mhz. Computer
running Windows 98 second edition.
Table 1: Selected STROBOSCOPE Symbols
SYMBOL
NAME
Queue
Normal
(activity)
Combi
(-nation
activity)
EXPLANATION
Is a holding place (buffer) for 0, 1, or several resources waiting to
become involved in the succeeding combination activity. Queues
may contain generic or characterized resources. The latter are
distinct from one another and they can be traced as individuals
through various network nodes during simulation. The logic
describing the ordering of resources upon entry into a queue of
characterized resources is termed a DISCIPLINE.
Describes a certain type of work to be done, or a delay, of a
known (probabilistic) duration from start to finish. May require a
single resource or no resource at all.
Like a normal, describes a certain type of work to be done, or a
delay, of a known (probabilistic) duration from start to finish.
Unlike a normal, requires several resources in combination for its
performance and draws what is needed from the queue(s) that
precede it.
Consolidator
Acts as a counter up to n (n is an integer value specified with the
node): after n resources have been released into the consolidator,
all n resources at once will be released from it.
Link
Shows flow logic. Should be labeled to meaningfully describe the
resources that flow through it. If the link emanates from a queue,
a DRAWORDER may be specified to sequence resources being
drawn from the queue.
Figure 12 depicts the STROBOSCOPE process model that corresponds to the value
stream map shown in Figure 8. The most relevant modeling assumptions are the
following:
a. The process model includes (1) a primary chain with RoutePipe1, Locate1, and
AnalyzeStress1 (surrounded by a blue solid box in Figure 12) and (2) a secondary
chain with RoutePipe2, Locate2 and AnalyzeStress2 (surrounded by a red dashed
box). For a specific project being studied, it is assumed that pipe supports will
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flow through the primary chain. The purpose of the secondary chain is to illustrate
that resources engaged in the primary chain also perform other work for other
projects.
b. The inputs and outputs of each task in the secondary chain are independent of
those of other tasks: they are decoupled (e.g., the output of RoutePipe2 does not
yield direct input into Locate2, whereas that of RoutePipe1 fed into Locate1) to
reflect that the amount of work designers have on different projects can vary
substantially.
c. The effect of batching is introduced only in the primary chain since the secondary
chain has been decoupled. This effect is included in the design and fabrication
phases using three different consolidator nodes called BatchRoute, BatchLocate
and BatchStress.
d. The duration of each task may vary over a range of values, which mimics
variability in the design of various kinds of pipe supports.
RoutePipe2
GENERATE
1 RouteTwo
PIPING ROUTING
AResource2
INIT 1
P4 ReadyLo
cate2
ARoute2
Info3
ATextFile3
INIT 100000
P5
F11
BatchLocate
BS=Variab le
Resourc
e2
LINK LABELS
Flow of Information 1
Flow of Information 2
Stress1
s1
ALocate1
AResource3
INIT 1
Locate2
P8
GENERATE
1 LocateTwo
Readyto
Stress2
Info4
ALocate2
ATextFile4
INIT 100000
PIPE SUPPORT LOCATION
Primary Chain
F
P
F12 Readyto F13 AnalyzeStres F16
CHARACTERIZED RESOURCES
TYPE
SUBTYPE
ATextFile1
InfoOne
ATextFile2
InfoTwo
ATextFile3
InfoThree
ATextFile4
InfoFour
ARoute1
RouteOne
ARoute2
RouteTwo
ALocate1
LocateOne
ALocate2
LocateTwo
BatchStress
BS=Variab le
F17
Done1
AStress1
Resourc
e3
P10
ATextFile2
INIT 100000
ARoute1
P6
P1
BS = Batch Size
Locate1
cate1
BS=Variab le
Resourc
e1
P2
Info2
F7 ReadyLo F8
F14
AResource1
INIT 1
BatchRoute
F9
ATextFile1
F6
GENERATE
1 StressOne
F15
RoutePipe1
Consolidate
LocateOnes
P11
F3
Info1
F4
AStart
INIT 1
F2
GENERATE
1 LocateOne
F10
Priority
F5
F1
Consolidate
RouteOnes
P3
Start
1
GENERATE
1 RouteOne
P8
GENERATE
40 InfoOne
P9 AnalyzeStres P12
Done2
s2
GENERATE
1 StressTwo
AStress2
PIPE STRESS ANALYSIS
Secondary Chain
CHARACTERIZED RESOURCES
TYPE
SUBTYPE
AResource1
ResourceOne
AResource2
ResourceTwo
AResource3
ResourceThree
AStress1
StressOne
AStress2
StressTwo
Figure 12: STROBOSCOPE Process Model of for Pipe and Pipe Support Design Tasks
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Implementation and Simulation of Supply Chain Tasks
Using Figure 12’s graphical representation of supply chain tasks, deterministic and
probabilistic simulation scenarios were implemented. The resources that remain constant
in these scenarios are:
a. The number of pipe supports to be designed for the project flowing through the
primary supply chain (represented by Info1) is equal to 40 units. This number
corresponds in order of magnitude to the number of supports that are engineered
to suit the main steam system of a power plant project. It is sufficiently large to
yield interesting simulation results yet sufficiently small for the simulation
processing time to remain small.
b. The number of pipe supports that enter the secondary supply chain is equal to
100,000 units. This number is set to be very high to reflect the assumption that the
design firm has a lot of work to do. We ignore the project schedules that define
due dates on any of their design tasks; otherwise, they would affect the
prioritisation of work.
c. The number of resources Resource1, Resource2, and Resource3 is set equal to 1
unit for all models. These resources will be shared by the primary and the
secondary chain in scenario 2.
Table 2 summarizes the two scenarios that are detailed next.
Table 2: Simulation Scenarios
Scenario
Type of Model
Chain
Focus
1
Deterministic
Primary
Batching
2
Probabilistic
Primary + Secondary
Batching/Variability/Multitasking
7.10.8.5
Scenario 1: Deterministic Model with Batching
The first simulation scenario illustrates the contribution of batching to lead time. Only the
primary chain with deterministic durations is considered in this model. This model serves
as a baseline for comparing behaviour against other, probabilistic simulation scenarios
that combine uncertainty, multitasking, and batching.
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Scenario 1 has been simulated considering different batch sizes as listed in Table 3. In
all cases, the durations of the tasks RoutePipe1, Locate1, and AnalyzeStress1 are 0.28
(2.25 mh / 8 mh = 0.2812), 0.06 (0.5 mh / 8 mh = 0.0625), and 0.26 (2.05 mh / 8 mh =
0.2562) working days per support respectively. These values represent the data shown in
Figures 8 and 11, converted into the equivalent number of working days per support
(Table 4).
Table 3: Model Parameters and Outputs for Scenarios 1 and 2
Simul.
Run
BatchRoute
[number of
supports]
BatchLocate
[number of
supports]
BatchStress
[number of
supports]
Scenario 1
Duration
[work day]
1
2
3
4
5
6
7
1
2
4
8
10
20
40
1
2
4
8
10
20
40
1
2
4
8
10
20
40
11.52
11.84
12.48
13.76
14.40
17.60
24.00
Scenario 2
Duration based on
100 simul. runs
[work day]
Mean
Standard
Dev.
11.69
11.88
12.54
13.72
14.45
17.52
24.01
0.32
0.29
0.30
0.31
0.30
0.23
0.34
Table 4: Activity Durations in Models for Scenarios 1 and 2
Task
Scenario 1
Task Durations
[work days / support]
RoutePipe1
RoutePipe2
Locate1
Locate2
AnalyzeStress1
AnalyzeStress2
0.28
n/a
0.06
n/a
0.26
n/a
Scenario 2
Task Durations
[work days / support]
Normal [mean, standard deviation]
Normal [0.28,0.05]
Normal [0.28,0.05]
Normal [0.06,0.01]
Normal [0.06.0.01]
Normal [0.26,0.05]
Normal [0.26,0.05]
The results of these simulation runs for scenario 1 are plotted in Figure 13. The relation
between batch sizes (which, for convenience were chosen to be the same for each of the
three tasks) and lead time here is linear. As is to be expected, the worst situation arises
when the batch size is equal to the total number of supports that enter into the system.
This situation results in the longest lead time. In this case, a batch size of 40 at each task
results in a lead time more than twice the lead time for a batch size of 1.
This plot demonstrates that batching is an important consideration in SC design
because the bigger the batch size, the longer the lead time of the process overall. While
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this finding is nothing new in the field of production management (e.g., Hopp and
Spearman 2000), design and project managers of construction project are not necessarily
aware of it, or, accordingly, consciously shaping batch sizes with SC performance in
mind.
40
B a t c h S iz e
( P ie c e s )
35
30
25
20
15
10
5
L e a d T im e
( W o r k in g D a ys )
0
0
5
10
15
20
25
30
35
40
45
50
55
60
Figure 13: Effect of Batch Size on SC Lead Time
7.10.8.6
Scenario 2: Probabilistic Model with Batching, Variability, and
Multitasking
Table 4 presents the probabilistic task durations that are used to simulate variability in the
system for scenario 2. For example, based on probability, a normal distribution applied to
RoutePipe1means that 68% of the time, the task duration will fall within the range
delimited by the distribution’s mean +/- standard deviation. Specifically, 68% of the time,
a duration will be greater than 0.23 (0.28-0.05) working days/support but less than 0.33
(0.28+0.05) working days/support.
Scenario 2 illustrates the impact of batching combined with variability and
multitasking on lead time. The secondary chain now has been added to the model in order
to mimic the effect of multitasking in the system. Table 3 presents the outputs from this
model corresponding to the batch-size combinations described in the same table and the
extreme case of 100% task priority (which, in effect, means no multitasking). This output
was computed using data from 100 random simulation runs.
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In reality, engineers multitask between two or more design processes. Multitasking,
then, needs to be controlled by execution priorities. In this scenario, the simulation engine
is programmed to share resources based on pre-determined priorities. Several simulations
have been run considering priorities ranging from 10% to 100%. Based on Figure 12,
priorities are assigned to tasks in the primary chain so that a priority value of 30% reflects
that when a resource becomes available, it will randomly select to work on that task 30%
of the time, and on competing tasks (tasks in the secondary chain) the remainder 70%.
Figure 14 illustrates that lead times generally increase with an increase in batch size
and with a decrease in priority of the primary chain. For example, a batch size of 30
supports and a priority of 80% for the primary chain (P = 0.8), results in an average lead
time of about 23 working days. A batch size of 30 but a priority of 50%, results in an
average lead time of 54 working days (more than double the previous lead time).
Figure 14: Lead Time (mean value ± standard deviation) vs. Batch Size for Different
Multitasking Priorities (P) of Primary SC, Using Data from 100 Random Simulation
Runs
Figure 15 shows the effect of multitasking from a different perspective. Clearly, lower
priorities yield increasingly longer lead times.
These models describe how a system for the delivery of capital projects can be
viewed as a series of tasks that depend on other tasks for handoffs occurring at discrete
times. In order to illustrate how handoffs affect SC performance, Figures 16 through 18
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graph the outputs of three different simulation runs showing the timing of handoffs
between tasks in the primary chain, based on different batch sizes and a 50% multitasking
priority or the primary over the secondary chain. Clearly, batching and multitasking
affect SC lead time.
Figure 15: Lead Time (mean value ± standard deviation) vs. Multitasking Priority of
Primary SC for Different Batch Sizes (B)
In terms of lead time, the ideal situation is created when the batch size for each task is 1,
so that the handoffs are frequent, the flow is smooth, and the overall SC incurs the least
delay. This ideal situation is not practical, though, because of setup times that make it
more rational for the ‘optimal’ batch (economic lot size) in any one process to be greater
than 1 unit.
Figure 16 illustrates simulation output when all task handoffs occur in unit batches of
1. It shows a lead time of 35 work days or 7 weeks. This is the shortest lead time
obtainable with the current configuration, but notice that the system is unbalanced: tasks
progress each at a different pace. The actual pace is indicated by the slope of each line in
Figure 16. The maximum possible pace is indicated by the duration of the task as given in
Table 4, for instance, Locate is the fastest task of all. Because RoutePipe is slower but
hands off an output to it, Locate can only go as fast as RoutePipe in this configuration.
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Figure 16: Lead Time vs. Number of Supports for Batches of 1 Support
Figures 17 and 18 illustrate the effect of batch size on performance in the primary supply
chain. Figure 17 considers three different batch sizes: respectively 10, 10, and 20
supports for the activities RoutePipe1, Locate1, and AnalyzeStress1 (these numbers were
chosen arbitrarily). Each vertical line in the chart represents an output batch being handed
off as input to the next task. For instance, figure 17 shows that Locate1 outputs units that
accumulate into a batch of 10 units relatively fast. Then, it has to wait until RoutePipe1
releases more output before it can work on the next batch handed to it. During this wait,
Locate1 multitasks with Locate2 in the secondary chain or simply remains on stand by.
Figure 17 shows that the larger batch sizes result in a larger lead time, now reaching 42
work days.
Figure 18 considers the largest possible batch size for this model, in this case 40
supports, resulting in a lead time of 59 work days, significantly greater than the 35-day
lead time obtained with unit handoffs.
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Figure 17: Lead Time vs. Number of Supports for Varying Batch Sizes (10 for
RoutePipe, 10 for Locate, and 20 for AnalyzeStress)
Figure 18: Lead Time vs. Number of Supports for Batches of 40 Supports
7.10.8.7
Summary of Simulation Findings
Computer-based simulation models were included in this case study in order to illustrate
how such modelling efforts can help in conducting what-if analyses to assess the
performance of alternative SCs, based on different configurations and management
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decision making (e.g., resource allocation and assignment of task priorities, reduction of
variability, and sizing of batch). The simulation models presented here were limited in
scope but could easily be extended to capture any additional complexity.
Note that prioritising tasks and, accordingly, allocating resources to multitask so as to
make best use of them is—in and by itself—not necessarily a bad practice. However,
scenario 2 illustrated that the randomness with which a person may switch from one task
to another is what interjects uncertainty into the system, and that uncertainty harms
overall throughput performance. In addition, the model does not include any penalty for
switching from one task to another one, though in reality there always will be some setup
or cleanup time associated with each switch. In any case, comparison of simulation
outputs can help to assess what the likely values would be of metrics when a specific SC
actually gets implemented.
The VSM shown in Figure 11 showed the direct work for each task per pipe support
and also the 40 work-day (8 weeks * 5 work days/week) total lead time to get a support
through the system. This direct work defined the task durations in the simulation models.
Given the direct work alone, and assuming no imbalances in task rates or batching or the
like, one might compute the lower bound on the total duration to get 40 supports through
the system: it is equal to 40*2.5 mh + 0.5 mh + 2.3 mh = 102.8 mh or 102.8 mh / 8
mh/day = 12.85 work days. The discrepancy between these 13 work days and the 40-day
lead time may be explained by a scenario like that depicted in Figure 17 (lead time of 41
days) that shows the effects of batching, variability, and multitasking on total lead time.
Of course, these explanations must be treated with caution, as they are not the only ones
plausible.
7.10.9 Supply Chain Improvements
7.10.9.1
SC Improvements Implemented to Date
SC improvement can be achieved by implementing any or all SC tactics as described in
Chapter 5 of this Research Report. The company that initiated this case study has
implemented several, namely:
1. Select a supplier for long-term collaboration on multiple projects and involve that
supplier early in design. The company in this case investigated alternative
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suppliers of supports for the kinds of capital facilities they consider to be part of
their core competence, then selected one and worked out a longer-term agreement
with them, which included (2) and (3). This agreement then eliminates a seven
week duration period normally required to issue an RFP to several pipe support
firms, receive and analyze bids, negotiate and award a P.O.
2. Standardize the design of pipe supports (standardize product design).
3. Use electronic data interchange and standardize engineering-supplier interface
processes (standardize process design).
Because hard data was not available to quantify performance metrics and document
actual SC improvement, figures 19 and 20 show speculative data on the improvements
that might be expected. Figure 19 presents a shortened version of the VSM depicted in
Figure 8. By selecting a supplier early, not only can most of the direct work (1-2
mh/support) associated with this task ‘Select Supplier and Send Info’ be taken out of the
SC, more importantly, the lead time associated with it (1 week) also gets taken out (see
the cross-out task in Figure 19). Thanks to product and process standardization, the
engineering firm as well as the supplier now spend less time on ‘Prepare Pipe Support
Drawings,’ “Analyze Engrg. & Prepare Budget,’ ‘Issue Pipe Support Details for Fab.,’
and “Approve Drawings’ (see the circled tasks in Figure 19). It is also likely that ‘Design
Pipe Support’ and ‘Fabricate’ are favorably impacted by standardization (see the dashedcircled tasks in Figure 19). Again, these changes not only remove direct work from the
SC, they also shorten the lead times corresponding to each task, and the latter has an even
greater impact than the former on overall reduction in SC lead time.
After implementation of these selected SC improvement initiatives, the total lead time
of 28-37 weeks, gets reduced by an estimated 20% to a range of 23-30 weeks. The total
amount of direct work has decreased by an estimated 7.5% and is down by 2.5-4.2 mh, so
that the ratio of value-added work/total lead time increases from 3.5-4% (Figures 8 and
19) to 4-4.3%% (Figure 20). Note that this ratio is still small and therefore suggests that
numerous other improvements yet remain to be implemented. Nevertheless, the gains in
lead time improvement, obtained thanks to the implemented SC tactics, are impressive.
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8 weeks
2-3
weeks
2-3
weeks
2 weeks
1 week
Design
Piping
System
Design
Pipe
Support
Check &
Modify
Other
Systems
Prepare
Pipe
Support
Drawings
Select
Supplier
and
Send Info
4.3-5.3 mh
0.5-1.0 mh
7-9.5 mh
1 mh
1-2 mh
Start
3 weeks
2 weeks
2 weeks
6-8
weeks
Analyze
Engrg. &
Prepare
Budget
Issue
Support
Details for
Fab
Approve
Drawings
Fabricate
1-2 mh
24 mh
0.5-1.1 mh
2-5 mh
1 week
Supports
Ready to
Ship
Deliver
Supports
On Site
1 mh
Total Lead Time = 29-33 weeks or 1160-1320 hrs (at 40 hrs/week)
Total Value Added Time = 42.3-51.9 hrs
VAT/Lead Time = 3.5-4%
Figure 19: Tasks Impacted by SC Performance Improvement Initiatives (Early Supplier
Selection and Involvement in Design, Product Standardization, and Process
Standardization)
Start
8 weeks
2-3 weeks
2-3 weeks
Design
Piping
System
Design
Pipe
Support
Check &
Modify
Other
Systems
4.3-5.3 mh
0.5-1.0 mh
7-9.5 mh
4-7 weeks
Engineer and Supplier Collaborate
3-8 mh
6-8 weeks
Fabricate
24 mh
1 week
Supports
Ready to
Ship
Deliver
Supports
On Site
1 mh
Total Lead Time = 23-30 weeks or 920-1200 hrs (at 40 hrs/week)
Total Value Added Time = 39.8-47.8 hrs
VAT/Lead Time = 4-4.3%
Figure 20: SC after Implementation of Selected SC Improvement Initiatives
7.10.9.2
On-going Improvement Efforts
To further improve SC performance, the company in this case study is now increasingly
using modularization and offsite assembly of entire structural steel bridges with complete
piping systems. These practices reflect a trend in the industry (e.g., Burke and Miller
1998, Schimmoller 1998, Gotlieb et al. 2001). Burke and Miller (1998) depict two
examples. Figure 21 illustrates a “modularized pipe rack being moved into place at the
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Mid-Georgia Cogeneration Plant. Piping, hangers, instrumentation, and the auxiliary
boiler deaerator are already integrated into the pipe rack modules.” Figure 22 illustrates
that “modularized pipe rack systems were incorporated into the design and construction
of the Cleburne Cogeneration Facility”
Figure 21: Modularized Pipe Rack at MidGeorgia Cogeneration Plan (photo courtesy
of Black&Veatch, reprinted in Burke and
Miller 1998)
Figure 22: Modularized Pipe Rack at
Cleburne Cogeneration Plan (photo
courtesy of Black&Veatch, reprinted in
Burke and Miller 1998)
The case-study company’s efforts are substantially motivated by a contract to
consecutively build five power plants of the same cookie-cutter design for one owner.
The use of reference power plants has been common in the EPC industry since the 1970s,
but the EPC firm’s ability to tie these products to SC process execution, including longerterm agreements with various suppliers, has traditionally been hampered by their inability
to forecast demand. Owners have a significant role to play in driving further SC
improvements of this kind, by providing EPC firms with transparency into their demand
forecasts and contracting for multi-project procurement SMC standardization will result
in a lower TIC.
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7.10.10
Conclusions
7.10.10.1
Case Study Conclusions
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This case study has illustrated that construction SCs are intrinsically complex and varied
by presenting alternative SC configurations that may be used in the delivery of pipe
supports used in power plants. Power plant owners and/or engineering firms may
independently or jointly select any one or several configurations to suit a specific
project’s requirements. Suppliers can significantly influence the shape of these SC by
offering a judiciously selected range of standardized products, showing willingness to
collaborate with designers on solution development, and possibly providing integrated
SC services for design, pipe support (and other plant component) fabrication, as well as
construction. A benefit of having several SC configurations to choose from is that the
abilities and constraints of SC participants can be balanced in order to achieve project
goals. Owners generally leave it up to the EPC firm and the supplier to manage the
selected configuration(s).
The presented case study has demonstrated that managing the interfaces between SC
tasks can yield significant performance improvements, not only by reducing the direct
work performed by SC participants, but more dramatically, by improving the way
handoffs occur from one task to the next. The application of value-stream mapping,
computer-based simulation, and metrics have shown to be useful tools to start SC
performance improvement initiatives. Gains of 20% reduction in SC lead time and 7.5%
reduction in direct work appear feasible thanks to the implementation of SC tactics such
as early supplier selection and their involvement in design, combined with product and
process standardization. The value-added time/lead time metric, found to have a value of
about 4% in this case study, suggests that there is significant opportunity for further
improvement.
7.10.10.2
Improvement Areas worth Further Investigation
A number of other SC tactics should be considered to achieve further improvement in
performance of the SC for pipe supports but a few stand out as worthy of getting priority
for further investigation.
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1. This case has focused on the SC of pipe supports, starting with piping system
design. The study has not sought out linkages and issues of synchronization
between parallel SCs such as those involving procurement and fabrication of pipe,
structural steel, or instrumentation, valves, and fittings; nor those pertaining to
delivery or matching of supports with other components needed in combination to
allow for installation at the site (e.g., Tommelein 1998). Nevertheless,
construction is a key beneficiary of excellence in SC execution. Data collection
regarding means to help synchronize SCs in light of design and schedule changes,
and further study of alternative SC configurations are in order to increase
understanding of these performance issues and recommend improvements.
2. Additional research is needed to relate modularization efforts to improved SC
performance.
3. A study is needed of the effect of ‘commoditization’ of engineering services as a
contributor to SC performance improvement (also see ENR 2002).
4. The emergence of the role of supply chain integrator and the value people in this
role bring to SCM must be recognized. This role must be defined in the context of
functions currently filled at the project- and corporate level within organizations
and at the supply-chain level across organizations.
References
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