Burn-in and Maintenance Policies

1994 ◽  
Vol 26 (01) ◽  
pp. 207-221 ◽  
Author(s):  
Jie Mi

Burn-in is a widely used method to improve quality of products after they have been produced. For a repairable component there are two common types of repair, complete repair and minimal repair. Preventive maintenance policies such as age replacement and block replacement are often employed in field operation. The present paper takes burn-in, maintenance and repair into consideration at the same time and considers related cost structures. The properties of the corresponding optimal burn-in times and optimal maintenance policies are discussed.

1994 ◽  
Vol 26 (1) ◽  
pp. 207-221 ◽  
Author(s):  
Jie Mi

Burn-in is a widely used method to improve quality of products after they have been produced. For a repairable component there are two common types of repair, complete repair and minimal repair. Preventive maintenance policies such as age replacement and block replacement are often employed in field operation. The present paper takes burn-in, maintenance and repair into consideration at the same time and considers related cost structures. The properties of the corresponding optimal burn-in times and optimal maintenance policies are discussed.


Author(s):  
Sukey Nakasima-López ◽  
Mydory Oyuky Nakasima-López ◽  
Karla Frida Madrigal Estrada ◽  
Erika Beltrán Salomón

Industries seek changes in manufacturing processes by designing or redesigning them, to improve the quality of products, reduce costs and cycle times, change materials, modify methods, design innovative products, among others. Facing these demands requires a powerful methodological framework known as Design of Experiments. Most of literature focuses on the application of these techniques in the areas of statistics and quality. However, the variety of problems facing engineers in industry is wide and includes different levels of complexity, ranging from the design of new products, improvement of design, maintenance, control and improvement of manufacturing processes, maintenance and repair of products, among others. This chapter provides the reader different applications of this methodology in industry, to highlight the importance and benefits of knowing and applying these techniques. It will present the application of this methodology in a general way and finally, it will discuss different case studies that use this methodology in industry.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
María Carmen Carnero ◽  
Andrés Gómez

Abstract Background The real-world application of maintenance in organisations brings together a number of maintenance policies in order to achieve the desired availability, efficiency and profitability. However, the literature mostly chooses a single maintenance policy, and so the decision process is not suited to the real conditions in the company to which it is applied. Our study takes a combination of maintenance policies as alternatives, and so conforms to the actual practice of maintenance in organisations. Furthermore, it introduces the possibility of including extra spare parts, or outsourcing maintenance policies. Although the selection of maintenance policies has been applied to many kinds of business and of machine, there is almost no instance of its application to hospitals, and it has never been applied to delivery systems for cytostatic drugs. Methods The model uses the fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), which is recognised as being highly suitable for solving group decision-making problems in a fuzzy environment. Fuzzy set theory is also considered to be more proficient than crisp numbers for handling the ambiguity, imprecisions, data scarcity, and uncertainty inherent in decisions made by human beings. The judgements required were obtained from a decision group comprising the heads of facilities maintenance, maintenance of medical equipment, health and safety at work, environment, and programming-admission. The group also included care staff; specifically, the heads of the main clinical services, and the medical supervisors. The model includes original criteria, such as Quality of health care, which measures impact on care as a function of mean availability of each alternative. It also considers Impact on hospital management via the criteria: Working environment in the organisation and Impact on health care; the former criterion measures equality among care services in the hospital, while the latter assesses the effect on regional health cover. The model was built using real data obtained from a state hospital in Spain. The model can also be easily applied to other national and international healthcare organisations, providing weights specific to the criteria. These are produced by a decision group from each healthcare organisation and the alternatives are updated in accordance with what is considered important in each hospital. Results The results obtained from the model recommend changing the alternative that is currently in use, Corrective and Preventive Maintenance, to Corrective and Preventive Maintenance plus two spare hoods. This alternative would lead to an availability of 1 (the highest possible) in the systems for preparing personalised cytotoxic drugs, and so the quality of service is therefore very high. Additionally, it could offer services to all the users of the hospital, and also offer cover in the preparation of cytotoxic medicines to other hospitals in the catchment area. Conclusions The results suggest the possibility that improvements to the support and logistical systems, which include maintenance, traditionally held to have no effect on quality of care, may be key to improving care quality, but also in reducing risk to patients, care and non-care staff, and the environment.


2011 ◽  
Vol 71-78 ◽  
pp. 4199-4202
Author(s):  
Bo Ya Zhao ◽  
Song Yang ◽  
Zhe Zhang ◽  
Ri Sheng Sun

In this paper an optimal maintenance policy for a Reactor Protection System (RPS) for a nuclear plant was developed. RPS consists of continuously operating sub-systems that were subject to random failures. A block system diagram for RPS had been proposed that facilitates analyzing of individual sub-systems separately. The proposed maintenance policy is the Age Replacement model, which incorporated both corrective and preventive maintenances. A Markov model was used to optimize the preventive maintenance interval of those sub-systems whose failure and repair rates were exponentially distributed. Finally, a sensitivity analysis had been performed and recommendations for maintaining the required RPS availability have been suggested.


Author(s):  
Binghai Zhou ◽  
Guoqing Cheng ◽  
Ziqiang Liu ◽  
Zilong Liu

This paper aims to integrate a two-period condition-based preventive maintenance (TP-CBM) into a pull production system by using Kanban control policy. The pull system is subject to continuous degradation and random failures. It is assumed that the system’s degradation can be divided into several stages, where the hazard rate increasing factor is introduced to describe the failure rate at each stage. Meanwhile, quality of products is also considered. Markov chain is used to formulate the process of degradation and periodic inspection policy is adopted to trigger the preventive maintenance. A mathematical model is proposed to obtain the optimal production control and maintenance policies, i.e. the inspection rate, the amount of Kanban and the preventive maintenance threshold. A genetic algorithm combined with integer programming is proposed to solve the problem. Numerical instances indicate that the proposed TP-CBM policy is effective and efficient.


1986 ◽  
Vol 23 (2) ◽  
pp. 536-542 ◽  
Author(s):  
Toshio Nakagawa

This paper considers periodic and sequential preventive maintenance (PM) policies for the system with minimal repair at failure: the PM is done (i) at periodic times kx and (ii) at constant intervals xk (k = 1, 2, ···, N). The system has a different failure distribution between PM'S and is replaced at the Nth PM. The optimal policies which minimize the expected cost rates are discussed. The optimal x and N of periodic PM and {xk} of sequential PM are easily computed in a Weibull distribution case.


2014 ◽  
Vol 1016 ◽  
pp. 802-806
Author(s):  
Onur Gölbaşı ◽  
Nuray Demirel

In recent decades, philosophy behind maintenance has varied consistently due to the changes in complexity of designs, advances in automation and mechanization, adaptation to the fast growing market demand, commercial computation in the sectors, and environmental issues. In mid-forties, simplicity of designs, limited maintenance opportunities, and immaturity of trade culture made enough to performonly fix it when it brokeapproach, i.e. corrective maintenance, after failures. Last quarter of the 21thcentury made essential to constitute more conservative and preventive maintenance policies in order to ensure safety, reliability, and availability of systems with longer lifetime and cost effectiveness. Preventive maintenance can provide an economic saving more than 18% of operating cost of systems. In this basis, various stochastic models were proposed as a tool to constitute a maintenance policy to measure system availability and to obtain optimal maintenance periods. This paper presents a general perspective on common stochastic models in maintenance planning such as Homogenous Poisson Process, Non-Homogenous Poisson Process, and Imperfect Maintenance. The paper also introduces two common maintenance policies, block and age replacement policy, using these stochastic models.


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