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Product configuration analysis
with design structure matrix
Product
configuration
analysis
P.T. Helo
Logistics Systems Research Group, University of Vaasa, Vaasa, Finland
997
Abstract
Purpose – Product configurator is a sales and production-planning tool that helps to transform
customer requirements into bills-of-materials, lists of features and cost estimations. The purpose of
this paper is to introduce a method of how to analyse sales configuration models by using a design
structure matrix (DSM) tool. By applying the DSM techniques, the sales configuration managers may
sequence the product configuration questions and organize the connection to production.
Design/methodology/approach – First, the paper explains a sales configuration system structure
from published academic and non-academic works. These sources employ both theoretical and
practical views on the topic of computer-based sales expert systems. Second, the paper demonstrates
an application of using DSM for configuration modelling.
Findings – The current sales configuration approaches include constraint-based, rules-based, and
object-oriented approaches. Product description methods vary, but the general problem remains the
same: the configuration process should be designed in such a way that customer selections do not
affect the previous selections. From the user point of view, answering the questions should be smooth
and fast. In turn this will lead to the growing importance of building more effective product
configuration models. DSM offers a systematic way to organise customer interface in sales
configuration systems.
Research limitations/implications – This paper analyses how DSM could help in planning
product configuration modelling. Comparison of different sequences is presented. The examples used
are hypothetical, but illustrate the suitability of DSM analysis. Companies are trying to establish easily
configured product models, which are fast, flexible and cost-effective for adjustments and
modifications. Use of DSM may help in the roll-out of sales configuration projects. DSM may also be
used as a quick view to represent the complexity of product configurability. The future needs for
configuration tools will be focused towards product model management from the technical limitations
of different data storage approaches.
Practical implications – Configurator software creates product variants, which are logical
descriptions of physical products. Variants have parameters which describe the customer-made
selections. The parameter selections may have interconnections between the choices. Some
selections may affect further selections and some combinations may not be allowed for
incompatibility, cost or safety reasons. There are several commercial software packages available
for creating product configurations. Product description methods vary, but the general problem
remains the same: the configuration process should be designed in such a way that customer
selections do not affect the previous selections. Answering the questions should be smooth and
fast. Configuration of complex products, for instance, airplanes, may include several sub-systems
and have various loops within the quotation process. The use of DSM may help in the roll-out of
sales configuration projects. DSM may also be used as a quick view to represent the complexity of
product configurability.
Originality/value – The paper helps both researchers and practitioners to obtain a clearer view on
the development of sales configuration systems and the potential of systematic DSM-based product
model analysis.
Keywords Sales information, Configuration management, Software tools, Manufacturing systems,
Integration, Design
Paper type General review
Industrial Management & Data
Systems
Vol. 106 No. 7, 2006
pp. 997-1011
q Emerald Group Publishing Limited
0263-5577
DOI 10.1108/02635570610688896
IMDS
106,7
998
1. Introduction
Configurators are software tools that allow a user to define a product that meets certain
given criteria by combining a number of parts, features or functions. In practice, a
configurator is a software application that is used in industry to enable quotation,
marketing, and rapid manufacturing of customised products. Industries are being
forced to move towards increasingly customised and individual products. In order to
do this cost effectively, the engineering phase needs to be accelerated.
The use of configurators decreases the engineering work required in the sales phase,
but also empowers the product development of platform derivative products (Franke,
1998). Configurators may be used for structural analysis, dimensioning or design
verification purposes. Manufacturing may use configurators for downloading the right
software on customer tailored embedded systems. After sales may check the sold
configuration and verify the compatibility of new installations or spare parts with the
current system.
Product configurators capture a lot of information related to engineering and
product pricing (Soininen et al., 1998). The relationships between parameters may be
very complicated and documenting these takes a lot of time and effort. Implementation
of project requires mapping the elements and their interactions. Creating a good
configuration depends on how good the map is. The map describes the selection route
from the requirements to the outcomes of configuration.
Configuration of complex products may include several sub-systems and have
various loops within the quotation process. In this paper, we analyse how design
structure matrix (DSM) could help planning product configuration modelling. The
remainder of this paper is as follows: firstly, basic types of product architectures are
introduced. Secondly, product-modelling techniques for configurations are reviewed
and feature-based configuration is presented with some examples. Thereafter, the use
of design structure matrices for configuration projects is discussed. Finally, the some
conclusions are drawn from DSM applications.
2. Product architectures
Product architecture is the way that functions are mapped to form a product (Ulrich,
1995). There are two generic types of product architectures, which are excluding each
other: these are integrated architecture and modular architecture. In the case of
modular architecture, each function is connected to a corresponding part, while in the
case of functional architecture; a part may have more than one function. A special case
of integrated architecture is adjustable architecture, which practically means that
there are controllable parameters that can affect the functionality of the product. For
instance, a PC computer is a flexible platform for various applications: the software
part adjusts the functionality of the machine. Products of modular architecture can be
combinations of the following types (Ulrich, 1995):
.
Slot. Components are connected with each other with an interface, which is not
necessarily interchangeable with other components. A car radio is a good
example of this: various radios can be installed in the slot. However, there are no
other components that could be mounted in the same slot.
.
Bus. Bus architecture is based on a standardized interface, which is common to
various parts. For example, the PCI bus in personal computers allows the
addition of modems, network cards, video card, etc. on the same type of rack.
.
Sectional. In sectional architecture, all interfaces are similar and there is no
common part where other parts would connect as in bus architecture. For
instance, SCSI interfaces in computers are connected to each other with a cable.
CD-drives, hard disks and other equipment can be in any sequence.
Modular architectures allow the flexibility for multi-purpose use. The cost efficiency
provided by a widely used platform is enhanced with modular structures (Meyer and
Lehnerd, 1997; Meyer and Utterback, 1993). All modular products are combinations
of these structures. However, there are also other ways to classify modular structures
(Yu et al., 1998). All modular architectures are connected to variant bill-of-materials
(BOM) when considering the modelling part of the process.
From the configuration point of view the product architecture describes how items
in BOM are connected with each other. A list of materials is a typical outcome of a
configuration process. The rules are given in the form of allowing and constraining
connections between items in some product configurators. These connections are very
similar to product architecture decisions.
3. Product modelling for variant products
Most of the product configurators are based on modelling variable BOM. This generic
BOM approach is used in many industries as a practical approach for implementation
of mass customization (Jiao et al., 2000). A product variant is a logical description of a
physical product. All derivative products can be described by product variants.
Variants have parameters, which make them different from other variants. For
instance, parameters for a car could include colour or engine type. There are several
commercial software packages available for creating product configurations. The
technical approaches for describing the rules are:
.
constraint based approach (Van Veen, 1992; Mailharro, 1998);
.
rules based approach; and
.
object-oriented approach (Ghatate et al., 2000).
Product description methods vary, but the general problem remains the same: the
configuration process should be designed in a way that customer selections do not
affect the previous selections. There are various techniques for describing product
variants. In this paper, we will briefly review:
.
BOM table;
.
logical tree; and
.
VAR-variant generator (Van Veen, 1992, p. 82).
3.1 Bill-of-materials table
BOM table is a tool for maintaining modular BOM. End products of the same kind can
be described by individual sequence of parameter values. According to this technique,
the table of BOMs consists of three major parameter types:
(1) Basic parameters. The same for all product variants {Lamp}.
(2) Variant parameter. Selection of several choices {Blue shade, black shade, white
shade}
(3) Option parameters. Choice type – yes/no {Shank}
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Basic parameters describe what basic structure will be used. Variant parameters
describe the selections within the basic structure. Option parameters are add-ons to
any product. The main difference between variant and option is that in order to specify
a product a value must be given for variant parameter, while the option value may be
nil. Variant parameter and option parameters are not depending on each other.
This type of configuration approach is limited. BOM table is able to support only
one-level BOM. In other words, there are no configurable sub-sets available. The lower
levels include a standardised structure, which cannot be effected by the higher-level
parameters. The use of this description method is suitable for the purpose where the
product is quite simple in terms of structure and the number of parameters is low. The
main benefit of this approach is that it is able to handle dependencies between
parameters and structural entities. The approach is also rather simple to learn.
3.2 Logical tree
Logical BOM-tree is another configuration approach. Logical diagram is a tree-based
description of BOM. This approach is beneficial when existing structures can be used
in creating new variations. In this method, logical nodes originating from Boolean
algebra are added into the structure. These nodes can be the following ones:
.
Product nodes (parts, components).
.
AND-nodes.
.
XOR-nodes.
.
Empty node (nil).
Product nodes are normal components, parts and items used in all traditional BOMs.
AND-nodes show which lower level trees are required for higher levels. In traditional
MRP-II software, pseudo-structures describe the same structure. XOR-nodes describe
the structures, where one must select one of the choices. An empty node does not have
any lower structures. It is used in cases where a XOR-node requires a lower level
structure. Figure 1 shows an example of using logical trees describing a table lamp.
Logical BOM-trees allow only item selection related choices. Use of descriptive
features that may affect several items are not allowed. By using this approach it is not
possible to use compatibility parameters such as “colour-red” that would change the
colour of all the parts that can be painted.
3.3 VAR-variant generator
A more advanced configuration approach is the VAR-variant generator. According to
this technique, all products can be described when the following conditions are met:
.
all parameters are independent of each other; and
.
product variants can be unambiguous if the parameter selection is made
accordingly.
BOM is described in a way that the main product X has specific lower level structures.
The lower level structure is not a standard item, but a set of parts, which have one or
more values. These sets are called clusters. Product X can be described by selecting one
expression of each cluster. The expression is selected according to a rule, which defines
the lower level parts (e.g. four doors in a car defines many lower level sub-structures).
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Figure 1.
Table lamp as a logical
tree
VAR-variant generator is able to handle not only single level BOM, but multi-level
BOMs as well (Van Veen, 1992, p. 88).
VAR-variant generator is based on relational database and can be implemented
with about 15 database tables. The approach is flexible for complex product models,
but on the other hand maintaining models takes a longer time to learn. The drawback
of VAR-variant generator is that it is not able to handle complicated connections such
as equations or function based rules (e.g. wire needed ¼ 3*pi*r pwrð2ÞÞ:
4. Feature based configuration
Many product configurators are based on a relation database model which restricts the
flexibility of use. New object-oriented techniques allow complex relationships which
are not limited to analysis of BOM (Simons et al., 2002). Feature-based configuration is
an approach where a distinction between product features (speed, type, size, etc.) and
items (part1, part2, part3) is made. The product architecture is a different issue
compared to the list of features. By using feature-based configurator the user may give
inputs such as:
.
the product should cost less than $30,000; and
.
the speed should be at least 150 km/h.
These parameters affect many choices and narrow the number of selections. By
fine-tuning some more detailed features the BOM can be created.
4.1 Concepts
The product variants are defined in feature-based configuration as product families. Each
family is an independent data item; it does not share any information with other families.
The family is a top-level data item; it includes all information valid for that family.
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The configurable data is arranged for a family in tabs, for example, feature groups. The
tabs include the same type of information that the user would like to see as at the same
screen. If the product is very simple there is need for just one tab. In most of the cases it is
reasonable to group the selections in tabs that include 4-6 choices. The following picture
gives an example of a product family that is defined to configure a motorbike. The
configurator engine shows the structure of the family and the user can change the order of
tabs or parameters and organize the data so that it is most usable (Figure 2):
.
Product family. A group of similar occurrences is called a product family.
A product family is always on the highest level of BOM and thus cannot be a
component for another product.
.
Parameter. Parameter is in relation with only product family, not to an
individual end-product. A parameter may have values: colour, type.
.
Parameter value. Value is an occurrence of property in parameters; for instance,
values for parameter “colour”: black, blue, white. The value of parameters
describes the parameter-value combinations that are allowed: colour-black,
colour-white, type-standard, type-customised.
.
Attributes. Attribute is a property connected to family level, parameter, value,
item. An attribute tool can be used for describing compatibility between
selections (110 V or 2), consumption of resource (e.g. these options will take
1,000 W of power, the power supply can feed 1,200 W).
.
Rules. Rules define allowed or denied combination of two or more attributes,
parameter values, BOM items or variables.
A feature-based product configurator can translate the product model into configurator
user interface. Figure 3 shows an example of feature-based configuration. Product model
details are input by the product model administrator. The user interface can be
generated automatically from features or tailored for custom web design. Finally, sales
engineers and the purchaser of the product may see the result in their configurator tools.
4.2 The rules for the family
The rules define how the values for each parameter are displayed. In a simple case the
configurator is just used to manage the family structure and there is no need to make
complicated rules. In that case both of the rules, for features and options, are allowed as
default. The basic rule types are:
Figure 2.
Examples of configuration
structure
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Figure 3.
Example of sales
configurator user interface
generated from product
model
.
.
.
deny a combination;
allow a combination; and
set value-based on a selection.
The setup of the rules depends on the number of restrictions the family might have.
In case most of the features are compatible, allowing combinations is the most
appropriate selection. If there is a situation where there are a lot of rules between the
parameters the denied model could be the case. Thus, if there are 200,000 variants and
just a few rules, one should use a deny type of model. And if there are hundreds of
possible variants and huge number of non-compatible constraints between the
parameters, then one should use the allowing type of model.
There may be two types of parameters: features and options. This enables you to
group the parameter to a group where there are a lot of correlations between the rules
and to a group where almost any option is valid. By making this analysis the product
modeller may decrease the number of required rules significantly.
The features are used when there are rules that define that, e.g. there should be
specific values for A and B to enable C to have certain values. In that case, C does not
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Figure 4.
Example of configuration
selection paths
have any values before the engine administrator allows the values for C to be displayed
for the specific combination of the rules of A and B. Typically in this case the features
use the denied model and only the values that are especially enabled are displayed. If
there is a case where parameter C has hundreds of values and only a few of them are
possible on a specific combination of A and B, then it is easier to disable all the choices
and enable only the few that are available. The options are typically parameters that
can be used for every parameter combination. In case of the options you deny a specific
combination of parameter values.
Figure 4 shows the usage of features and options. All the possible values for the first
feature A are available. But only after selecting a1, a2, or a3 b1, b3 and b4 are available.
Then a combination of {(a1, b1), (a2, b2), . . . ,(a3, b3)} enables the values c1, c2, c3, c4, c5
and c6. In the engine we call the blue enables sources and green results targets. So there
is no value for parameter H if no predecessor has allowed values for the parameter.
In case of options the engine allows the denial of specific combinations. After
selecting value 3c in parameter 3 the user cannot select values 8d or 8j for parameter 8.
There can be relations between features and options as well. The above example denies
after selecting g2 the selection of 7a or 7c.
The product modeller should keep the rules as simple as possible and be sure to
check out the rule type for the selected parameters. There is no sense to allow
combination 6a ! 9b, because parameter 9 is type option and all the values are
allowed as default so the rule is useless. Feature-based configuration is a flexible
platform for building product models. Building a map of interactions between different
parameters and items takes the majority of time in any product configuration project.
5. Design structure matrix
DSM is an approach used for system analysis of decomposition and integration. DSM
is a square matrix showing interactions flow between elements. The elements may
present components of a product, phases of product development, people in
organisations or design parameters of a product (Browning, 2001; Smith and Eppinger,
1997). This method introduced by Steward (1981) has been used in many industrial
applications. The examples mentioned in the literature include design of automobiles,
design of jet engines and design of a microprocessor (Ulrich and Eppinger, 1994).
The main idea of DSM is to map the interactions into a matrix, where elements are
listed on the diagonal. Off-diagonal on the lower side represents information flow that
feeds the following elements; the upper side indicates that the element feeds something
back upstream. Figure 5 shows three basic types of relationship between configuration
elements A and B. The first type is a “parallel” relationship, where elements not
depending on each other may be processed separately. The second type is “sequential”
where element B depends from the input fed from element A. The last stereotype,
“coupled” refers to a set where elements depend on each other. A change in element B
has an effect back to A. This cyclic dependency is called “circuits”. In the configuration
context, the elements may be features describing the products, items that make BOM,
or related to variables which allow advanced calculation of configuration outcomes
(for example, weight and power consumption).
The use of DSM with configurations is two-fold. In one-level configurations, the
main objective is to sequence features in a way that first selection is the most
restrictive question, and the last questions are not having effect on those parameters
already input. There is a greater need for DSM in multi-level configurations where the
challenge is to capture the possible feedback loops and try to formulize
sub-configuration elements. There are several analytical approaches for organising
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Figure 5.
Stereotypes of system
configurations
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matrix. However, in many cases the matrix representation itself helps to re-organise
the feature questions in an applicable sequence. Rules describe the system element
interactions. The possible combinations include interactions between:
.
Features. Parameters and possible values, e.g. colour – green. Feature selections
may affect other features. For instance, all colours may not be available in every
size.
.
BOM. Items that describe the product architectures.
.
Variables. Outcomes of advanced calculations. E.g. weight of product, power
consumption of configured system, sales price or cost structure.
Figure 6 shows an example of DSM showing the elements and their dependencies on
the configuration model. Complex configuration models that include configuration in
several levels are challenged by the questions: how should one organise the
sub-configurations? Which feature selections are common to all configurations, which
features are connected to only one sub-system? Clustering of the DSM creates groups of
features, BOMs and variables that should be handled together. This kind of entity is a
clear sub-configuration. By using tearing and partitioning, the product modeller
smooths the actual configuration process by removing unnecessary feedback loops.
In order to demonstrate how a traditional process flow diagram may be converted to
a DSM matrix, consider the example shown in Figure 7. From the user point of view the
configuration process starts from the top. The sequence is pre-defined and there are
several incompatibilities between different selections, which could be
recommendations or denying. Figure 8 shows the same process described as DSM
presentation. At the upper side of the diagonal, the possible feedback loops in the
configuration process are visible and the feed-forward components are shown at the
lower side. The sequence of process elements could be adjusted manually or by using
advanced automatic clustering systems provided by many DSM software packages.
The result of the analysis can show potential time delays in the order-fulfilment
Figure 6.
Example of configuration
DSM showing interactions
for features, BOM and
variables (Problematics.
DSM software screenshot)
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Figure 7.
Example of selection
dependencies in computer
server configuration
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Figure 8.
DSM example of
configuration system
process from the sales engineering point of view and suggest improvements for the
product architecture as well.
6. Conclusions
The configuration projects are very important for today’s companies achieving
improved response. There is an obvious need to integrate the intra-organisational data
systems such as sales and production (Kumar and Meade, 2002), production planning
and purchasing (Rantala and Hilmola, 2005) as well as inter-organisational systems
such as supplier relationships and logistics (Tarn et al., 2002; Helo and Szekely, 2005).
The examples from high clock speed industries, such as electronics manufacturing,
have shown that the key issue in successful production management is to apply the
new technologies for processes as well (Helo, 2004). Seamless integration between
product engineering and supply chain management may be achieved by using
automated configuration systems. For this reason, systematic approaches are needed
to help managers build configuration processes. This paper has contributed on
suggesting the application of DSM methodology for designing this integration. These
methods may be used when companies are moving towards flexible structures and
agile virtual environments (Ma and Davidrajuh, 2005).
Feature-based configuration and other object-oriented techniques allow great
flexibility in creating product models. Because of these advances in software
engineering, the challenge of building models is no more a technical issue but an issue
of managing the configuration process. The process may incorporate different
companies and logistics operations such as production planning and supply chain
management (Helo and Szekely, 2005; Hsu and Chen, 2004). Configuration is typically
related to sales, but it has important links to engineering, too, such as product
design. The nature of selling technical products is iterative, several reviews are
required before the final configuration is frozen. The key requirements for a modern
configurator are:
.
.
.
flexible modelling features;
smooth configuration process with minimum number of feedbacks; and
easy to learn product modelling.
These requirements have a direct connection to strategic objectives such as profitable
variety management. The companies applying sales configuration tools are trying to
establish easily configured product models, which are fast, flexible and cost effective
for adjustments and modifications. Use of DSM may help in roll out of sales
configuration projects. DSM may also be used as a quick view to represent the
complexity of product configurability.
An analytical approach such as DSM should provide a more quantitative basis for
mass customization and product design strategies. The idea of mass customisation is
that a factory is able to produce one-of-a-kind products with high quality and fast
delivery with a low cost of mass production. The drivers enabling this are new
technological manufacturing applications and advances in designing procedures.
According to Pine (1993):
At its core is a tremendous increase in variety and customisation without a corresponding
increase in costs. At its limit, it is the mass production of individually customized goods and
services.
Use of a product configurator allows maintaining an extensive product variety without
remarkable reductions in productivity. Since, the beginning of the 1990s various mass
customisation applications have been presented (Anderson, 1997; Pine, 1993).
Design-for-manufacturing has become an important research area in product
development as well as the use of product platforms. Despite the innovations,
manufacturers are still balancing between time-to-market, product variety and unit-costs
(Tseng and Jiao, 1998). Tools for assessing the trade-off between these parameters are
required. In practice, the challenges are related to the management of the following issues
(Tseng and Jiao, 1998):
.
measurement and implications of reusability/commonality of parts and products
(Jiao and Tseng, 2000);
.
designing product platforms for cost-effective customisation; and
.
integrated product development for managing the during the product
life-cycle.
Contemporary mass-customisation tools such as product configurators are typically
built based on variable BOM, which are able to deal with technical constraints given in
rule tables. Product modelling techniques have been developed in engineering design
and industrial software design. The aim in engineering design has been to introduce
tools for modular architectures. One of the major challenges has been flexible designs
for manufacturing. Typically, this is derived by assumed market information,
technological constraints and manufacturing related constraints (Tseng and Jiao, 1998;
Yu et al., 1998).
DSM is a powerful approach providing help for product model builders to make a
map of interactions between features, BOM items, and design variables. By using
this kind of configuration sequence analysis, the end-user of the sales configurator
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logistics into account in product design is a strategic insight. This results in more
powerful automated sales tools for industry and possibility for true mass
customization.
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Further reading
Davis, S.M. (1987), Future Perfect, Addison-Wesley, Reading, MA.
Krishnan, V., Eppinger, S.D. and Whitney, D.E. (1997), “A model-based framework to overlap
product development activities”, Management Science, Vol. 43 No. 4, pp. 437-51.
Corresponding author
P.T. Helo can be contacted at: petri.helo@uwasa.fi
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