Spare Part
Management
By Smita Sharma
S
What is a Spare and why it is
needed?
S Manufacturing Process comprise complex equipment
with thousands of subassemblies and discrete parts.
Parts and sub assemblies of machines will eventually
require repair and replacement.
S Increased efficiency of production plants requires
minimization of machine downtime. However, we don’t
know which machine part will fail when? Therefore ,
availability of a wide range of spare parts is major factor
for reduction in downtime when a breakdown occurs.
What is a Spare and why it is
needed?
S A logical approach to solve the issue of spare parts
availability lies in stocking large quantities of spare parts
for immediate use whenever needed.
S On the other hand stocking is limited by space and cost.
S Therefore designing a system and managing spare part
in an optimal way represents a critical and important task.
Objectives
1.
Discuss the different classifications of service parts
2.
Analyse the importance of spare part management
3.
Explain how maintenance policies impact maintenance economics
4.
Analyse mathematical models for spare parts decision making
5.
Define classification and other models for spare part decision making
6.
Discuss the major issues in optimally managing spare parts
7.
Assess the success factors of spare parts management
Basics of Spare parts
management
S
Spare parts and services account for 8 percent of the annual gross
domestic product in the United States.
S
Spare parts management is the process of planning and aligning service
parts inventories, resources and processes to ensure optimal customer
service and response with minimal risk and cost.
S
Spare parts management embraces three different kinds of service spare
parts.
1.
First Party Spare parts
2.
Second Party Spare parts
3.
Third Party Spare parts
Basics of Spare parts
management
S Each type of service part also reflects a different types of
control situation. On this basis service spare parts can
further be subdivided into two main categories:
1.
2.
Repairable
Non repairable or disposables
S Spare part management is at the heart of any effective
service operation. Service operation depends on the
knowledge about the failure behavior of the system and
the ability to project the demand.
The Economics of Service
parts
S Spare parts inventory value is important. The issue is to
have the right parts, at the right time, so that either plant
utilization or revenue generation is not negatively
impacted.
S How can spare parts management be turned into a
competitive advantage?
S Which service parts have to be stocked?
S Where are the service parts to be stocked?
S How many of them to be kept in stock for each of these
service parts?
Economies of Maintenance
S As spare parts management is directly related to
maintenance, we first need to understand maintenance
economics.
S Some of the common approaches to maintenance are;
1.
2.
3.
4.
Breakdown Maintenance
Preventive maintenance
Predictive maintenance
Proactive mantenance
Economies of Maintenance
S Cost of Maintenance: Total cost due to failure of an
equipment will be;
1.
2.
3.
4.
5.
6.
Cost of lost sales
Cost of idle labour both direct and indirect
Cost of delays in downstream process
Cost of scrap, wastage and rejection
Start up cost
Cost of customer dissatisfaction due to delays
Economies of Maintenance
S A good Maintenance Policy ensures
1.
2.
Expediting the entire maintenance task and eliminating
delays by applying sound system and methods, adequate
maintenance facilities, well trained crew etc.
Minimizing breakdowns by installing a suitable preventive
maintenance system and scheduling maintenance jobs
during non production shifts
Decision models
Efficient and cost effective service operations hinge on the ability
of the organization to accurately plan inventories and service
parts.
1.
2.
3.
Avoid excess inventories
Maintain required service levels
Avoid stock outs
When looking at demand processes, much depends on the
context we are considering. First party and second party spares
are sourced from OEM. For third party spares, experience with
comparable service parts plays an important role.
Decision models
There are two main approaches followed to develop possible
spares provisioning decision models:
1.
Mathematical model
2.
Classification approaches
Mathematical Models
S The first approach concerns the development of
mathematical models based on linear programming ,
dynamic programming, goal programming, simulation etc.
S Mathematical models generally concentrate on the
mathematical optimization of the inventory costs and
service levels associated with a potential spares
inventory policy in terms of economic order quantity,
reorder point and safety stocks.
Mathematical Models
S A mathematical optimization of inventory costs is a
difficult task in the case of spare parts.
S Standard methods of inventory control fall short of finding
adequate solutions.
S Common statistical models for inventory control lose their
applicability when historical demand figures are
unavailable or invalid.
Mathematical Models
S The control of service part is complex matter. Many of the
models evolved are too complex, abstract or oversimplified.
S These models do not consider several intangible factors, such
as obsolescence, standard characteristic of the item, type and
quality of suppliers, etc..
S The models assume demand to be constant or stationary,
following a Poisson process.
S For fast moving items theoretical safety stock can be calculated
using statistical theory
Classification models
S Considering the limitations of mathematical models, the
use of classifications system as a spare parts
management tool represent a popular approach in
industry.
S
Service parts are expensive, demand is erratic and
hence hard to predict, delivery times are long and
stochastic and customers want their service parts
quickly.
Classification models
S In order to approach the problem a criticality classification of
spare parts is generally used. Most classification models are
based on this and on this administrative efficiency
considerations
S Some of the classification criteria are:
1. Criticality of the function to be performed by a system that
2.
3.
4.
become defective
Price
Delivery time
Life cycle phase of the service part
Classification models
S ABC Classifications This is perhaps the most well known and
used classification system for inventory management. This is
based on Pareto’s principle. After calculating rupee usage for
each inventory item, the items are ranked by rupee usage, from
highest to lowest. The first 20 % are assigned to class A, the
next 30 % items are classified as class B and finally the last
50% items are C class items
S Attributes which have intangible aspects such as safety
objectives, provisioning characteristic, type of maintenance
adopted, loss of production etc. cannot be included.
Classification models
S VED classification: This is the most commonly used classification
system for spare parts inventory management . When used in
combination with other techniques, it is generally quite effective.
Here parts are called vital, essential and desirables.
1.
Vital parts: Items that cause high losses due to non-availability
of equipment. In case they are needed while not in stock.
2.
Essential parts: Items that cause moderate losses due to nonavailability of equipment, in case they are not in stock
3.
Desirable parts: Items that cause minor disruptions, in case
they are needed while not in stock.
Classification models
S A systematic procedure that could be helpful here is the
Analytic Hierarchy process (AHP). This multi criteria
decision making tool finds the relative priorities or weights
to be assigned to different criteria and alternatives which
characterize the spare part decision.
S Both qualitative and quantitative aspects need to be
considered. Critical aspects of a problem are organised
into hierarchical structure similar to a family tree. *
formula can be discussed later
Classification models
S The AHP approach is characterized by some important
properties:
1.
It makes possible to tackle the problem in a complete and
thorough way taking several factors in to account
2.
A direct quantitative judgment of the relevant factors is not
required
3.
AHP analysis can also handle qualitative judgments
4.
Its result can be evaluated performing a sensitivity analysis.
Issues regarding Service
parts
1.
Lack of visibility into service parts inventory levels
2.
Disparate sources of service part data
3.
Inconsistent naming conventions for service parts and
suppliers
4.
Disconnected inventory planning and execution procedures.
5.
Insufficient and fragmented use of automated and advance
analytics.
Success factors
1.
Align and coordinate service parts planning and operations
across an extended service network.
2.
Leverage alternate service providers: pooling, standardization
and outsourcing of service parts management to logistics
service providers are the most successful strategies
3.
Aggregate, classify and enhance service parts data
4.
Automate service parts planning and execution activities.
Thank you!
S