Purpose – The purpose of this paper is to provide a brief overview of condition based maintenance (CBM) with definitions of various terms, overview of some history, recent developments, applications, and research challenges in the CBM domain.Design/methodology/approach – The article presents the insight into various maintenance strategies and provides their respective merits and demerits in various aspects. It then provides the detailed discussion of CBM that includes applications of various methodologies and technologies that are being implemented in the field. Finally, it ends with open challenges in implementing condition based maintenance systems.Findings – This paper surveys research articles and describes how CBM can be used to optimize maintenance strategies and increase the feasibility and practicality of a CBM system.Practical implications – CBM systems are completely practical to implement and applicable to various domains including automotive, manufacturing, aviation, medical, etc. This paper p...

Condition based maintenance: a survey

https://pure.tue.nl/ws/files/3573376/377143011120502.pdf

System-oriented inventory models for spare parts

Industrial maintenance decision-making: A systematic literature review

Joint condition-based maintenance and inventory optimization for systems with multiple components

Product reliability in the field is important for a wide variety of critical applications such as manufacturing, transportation, power generation, and health care. In particular, the propensity of achieving zero-downtime emphasizes the need for Remaining Useful Life (RUL) prediction for a single unit. The task is quite challenging when the unit is subject to time-varying operating conditions. This article provides a framework for predicting the RUL of a single unit under time-varying operating conditions by incorporating the results of both accelerated degradation testing and in situ condition monitoring. For illustration purposes, the underlying degradation process is modeled as a Brownian motion evolving in response to the operating conditions. The model is combined with in situ degradation measurements of the unit and the operating conditions to predict the unit's RUL through a Bayesian technique. When the operating conditions are piecewise constant, statistical approaches using a conjugate prior distr...

A framework for predicting the remaining useful life of a single unit under time-varying operating conditions

Throughput of a manufacturing process depends on the effectiveness of equipment maintenance, and the availability of spare(service) parts. This paper addresses a joint production and spare part inventory control strategy driven by condition based maintenance(CBM) for a piece of manufacturing equipment. Specifically, a critical unit is continuously monitored for performance degradation during operation. The amount of degradation is utilized to initiate replacement actions in conjunction with spare part inventory control under both production lot size, and due date constraints. A degradation limit maintenance policy is combined with a base stock spare part inventory control policy to manage the manufacturing process. The objectives are to minimize the spare part inventory, and the expected total operating cost. Constrained least squares approximation, and simulation-based optimization are utilized, in a heuristic two-step approach, to determine the optimal base-stock level of spare parts, along with the preventive maintenance threshold. The resulting joint decision ascertains the allowed stockout probability for spare parts, while incurring the minimal operating cost for the required production within a fixed production duration. A case study of an automotive engine manufacturing process is provided to demonstrate the proposed decision-making methodology in practical use.

Joint Production and Spare Part Inventory Control Strategy Driven by Condition Based Maintenance

The ability to predict and prevent equipment failures is essential for managing a manufacturing process. Once failure symptoms are detected, timely maintenance needs to be performed with the support of required spare parts. However, the availability of spare parts often becomes the bottleneck of process throughput, and sometimes expensive emergency orders of spare parts have to be placed to meet a production due date. This paper addresses a joint production and spare part inventory control strategy driven by condition based maintenance (CBM) for a piece of manufacturing equipment with a critical unit. Specifically, the amount of degradation of the unit is monitored continuously during operation and used to drive replacement actions and spare part inventory control under both production lot size and due date constraints. A degradation limit maintenance policy and a base-stock spare part inventory control policy are integrated to manage the manufacturing process. The objective is to ascertain the service level for spare parts while minimizing the total operating cost. To determine the optimal base-stock level of spare parts and maintenance threshold, a two-stage approach using constrained least square approximation and simulation-based optimization techniques is developed. An automotive engine manufacturing process is provided to demonstrate the use of the proposed decision making strategy.

Spare part inventory control driven by condition based maintenance

The problem of effectively integrating condition based maintenance and spare part inventory control is studied and a solution methodology demonstrated. Degradation modeling, Bayesian analysis, and optimization techniques are utilized to define a condition based maintenance model for a single production system under spare part inventory constraints. Specifically, the gamma process is used to model the degradation process for a system that has a monotonically increasing degradation behavior. The initial gamma process parameters are inferred during product testing and utilized to define a spare part optimization model. This optimization model is used to ascertain the stockout probability to support the system. To address the uncertainty in parameter estimates, the gamma process parameters are updated through a Bayesian updating technique as more degradation data is collected over time for a real time remaining useful life prediction of the component. Finally, condition based maintenance and spare part inventory control are tied together into a overall production decision model. The production decision model generates an optimal degradation limit maintenance policy which provides a means to make component replacement decisions while addressing the relationship among outstanding orders, the number of spares, and the degradation state. One can see that the methodology developed in this thesis effectively ties together condition based maintenance, production, and spare parts inventory control. This body of work is important in the area of reliability and maintenance engineering since it provides a way of
controlling spare parts in conjunction with condition based maintenance and production. This concept addresses a relationship which is not well developed in the literature, yet has a significant practical value.

Condition based maintenance of a single system under spare part inventory constraints

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Joint Production and Spare Part Inventory Control Strategy Driven by Condition Based Maintenance

Spare part inventory control driven by condition based maintenance

Condition based maintenance of a single system under spare part inventory constraints