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Spare Part Management

By Smita Sharma

What is a Spare and why it is needed?

Manufacturing Process comprise complex equipment with thousands of subassemblies and discrete parts. Parts and sub assemblies of machines will eventually require repair and replacement.

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?

A logical approach to solve the issue of spare parts availability lies in stocking large quantities of spare parts for immediate use whenever needed.

On the other hand stocking is limited by space and cost.

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 parts2. Analyse the importance of spare part management3. Explain how maintenance policies impact maintenance economics4. Analyse mathematical models for spare parts decision making5. Define classification and other models for spare part decision making6. Discuss the major issues in optimally managing spare parts 7. Assess the success factors of spare parts management

Basics of Spare parts management

Spare parts and services account for 8 percent of the annual gross domestic product in the United States.

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.

Spare parts management embraces three different kinds of service spare parts.

1. First Party Spare parts2. Second Party Spare parts3. Third Party Spare parts

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. Repairable2. Non repairable or disposables

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.

Basics of Spare parts management

The Economics of Service parts

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.

How can spare parts management be turned into a competitive advantage? Which service parts have to be stocked? Where are the service parts to be stocked? How many of them to be kept in stock for each of these service

parts?

Economies of Maintenance

As spare parts management is directly related to maintenance, we first need to understand maintenance economics.

Some of the common approaches to maintenance are;1. Breakdown Maintenance2. Preventive maintenance3. Predictive maintenance4. Proactive mantenance

Economies of Maintenance

Cost of Maintenance: Total cost due to failure of an equipment will be;1. Cost of lost sales 2. Cost of idle labour both direct and indirect3. Cost of delays in downstream process4. Cost of scrap, wastage and rejection5. Start up cost6. Cost of customer dissatisfaction due to delays

Economies of Maintenance

A good Maintenance Policy ensures1. Expediting the entire maintenance task and

eliminating delays by applying sound system and methods, adequate maintenance facilities, well trained crew etc.

2. 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. Avoid excess inventories2. Maintain required service levels3. 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 model2. Classification approaches

Mathematical Models

The first approach concerns the development of mathematical models based on linear programming , dynamic programming, goal programming, simulation etc.

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

A mathematical optimization of inventory costs is a difficult task in the case of spare parts.

Standard methods of inventory control fall short of finding adequate solutions.

Common statistical models for inventory control lose their applicability when historical demand figures are unavailable or invalid.

Mathematical Models

The control of service part is complex matter. Many of the models evolved are too complex, abstract or oversimplified.

These models do not consider several intangible factors, such as obsolescence, standard characteristic of the item, type and quality of suppliers, etc..

The models assume demand to be constant or stationary, following a Poisson process.

For fast moving items theoretical safety stock can be calculated using statistical theory

Classification models

Considering the limitations of mathematical models, the use of classifications system as a spare parts management tool represent a popular approach in industry.

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

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

Some of the classification criteria are:1. Criticality of the function to be performed by a system that

become defective2. Price3. Delivery time4. Life cycle phase of the service part

Classification models

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

Attributes which have intangible aspects such as safety objectives, provisioning characteristic, type of maintenance adopted, loss of production etc. cannot be included.

Classification models

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 non-availability 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

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.

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

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 judgments4. Its result can be evaluated performing a sensitivity analysis.

Issues regarding Service parts

1. Lack of visibility into service parts inventory levels2. Disparate sources of service part data3. Inconsistent naming conventions for service parts and

suppliers4. 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 data4. Automate service parts planning and execution activities.

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Thank you!