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Maintenance is not usually noticed in the context of quality. Some quality philosophies recognize that production equipment must be maintained in order to manufacture quality products. So‐called quality gurus have not emphasized that maintenance could have a significant role in quality. The studies on maintenance have concentrated on the cost effects. There is no idea what could be the magnitude of maintenance on quality deficiencies in different industries. The study carried out in five Finnish industries revealed that, in the process industries, maintenance is usually among the three most important reasons why there are quality problems. In the heavy industries utilizing continuous processes maintenance seems to have the highest impact on quality.

Points out that the concepts of total productive maintenance (TPM) were formulated by combining the principles of total quality control (TQC) and maintenance engineering. Claims that the theory of TPM is not yet exhaustive. Proposes a model called “strategic maintenance quality engineering” (SMQE) to make the theory of TPM exhaustive. Deals with the last phase of SMQE which envisages the evaluation of each cycle of SMQE performance. Applies benchmarking with suitable modifications to carry out the last phase of SMQE. Presents the salient features of pilot implementation study conducted in two companies. Suggests that the use of information technology (IT) for benchmarking SMQE would aid in improving strategic maintenance quality more effectively.

In this article a model is presented concerning the organisation of the maintenance process of a quality system. This model consists of the composition of two existing models. The point of departure is a three‐level model of quality management. Then each of these three levels has been split up into two components called “system‐structural” and “social‐structural”. After introducing several maintenance concepts on a conceptual level, these concepts are applied to each of these levels and components.

Focuses on the relationship between maintenance and quality. Then briefly reviews models relating production and quality on the one hand, and production and maintenance on the other. Using concepts from predictive maintenance and the measure of equipment effectiveness from total productive maintenance (TPM), identifies explicit links between maintenance and quality. Emphasizes the need to develop adequate models relating maintenance and quality. Presents two approaches for modelling the link between maintenance and quality. The first approach is based on the concept of imperfect maintenance and the second one uses the Taguchi approach to quality and maintenance.

Factory management needs to find the technically feasible point up to which maintenance and quality activity levels of a factory should be selected to achieve highest productivity with a view to fulfil company objectives for higher profitability. This research paper aims to report the development of an analytical relation between maintenance, quality and productivity.

An analytical relation is designed and developed incorporating graphical analysis and regression analysis to support outputs of graphical method, which creates an appropriate model. A mixed research approach is used, including application of a practical case example.

The study displays a wide range of productivity performance profiles with the strategic aim of identifying the technically feasible highest productivity result obtained. It has formulated an important analytical link, and suggested a few recommendations. The formulated model predicts the best possible productivity result out of maintenance and quality‐related practical data of a factory. The analysis enables managers to analyze, compare and identify improvement opportunities in order to enjoy competitive advantages.

Modern factory managers, particularly in food production, who live in a world of rapid changes, extensive interactions and complex situations, and face everyday challenges in a competitive global market, can use this model as a hands‐on tool for measurement, evaluation, logically better and proper realistic planning and implementation of maintenance and quality activities to attain maximum manufacturing productivity for their companies.

The model is the result of an attempt to design and develop, fulfil identified technical managerial needs and offer practical help to make logical decisions. Evidence from the literature confirms that this is a newer outlook on analytical diagnostic tools, which demonstrates the weaknesses in existing factory production system and thus helps in identifying key areas for productivity improvements. Therefore, this research is one step to further the potential and practical value added contribution in food and other industries.

Claims that the concepts of Total Productive Maintenance (TPM) fundamentally aim at applying Total Quality Management (TQM) philosophy in maintenance engineering. Emphasises the need of incorporating quality system and its monitoring to enhance maintenance quality. Points out that QS 9000 standard is expected to be a future quality system model in enterprises. Describes the design features of maintenance quality system model that has been developed based on QS 9000 standards. Cites the need of using continuous and economical knowledge which is possible only through the careful exploitation of information technology. Briefs the design of a knowledge base system and the development and performance of its pre‐auditing module. Presents a few sample screen outputs of this module. Concludes by suggesting the ways of productively exploiting the pre‐auditing module of the knowledge base system.

Over the past few years, considerable attention has been focused on the implementation and usage of quality improvement and related techniques to the service industry. Reports on an ongoing project to implement a quality maintenance system (QMS) in a military maintenance organization. Total quality management (TQM) concepts are applied as a management tool to improve the quality of maintenance services. Identifies and analyses the nature of the maintenance problem and its causes using data collected over 12 months. Finds that the low serviceability rate of vehicles needs to be improved. Indicates that TQM concepts can be applied effectively to maintenance services. Although the impact of the QMS has not been fully felt, employee participation, education and supervision surfaced as critical success factors during this stage of the implementation process.

The purpose of this study is to develop a joint production, maintenance and quality control strategy involving a periodic preventive maintenance policy.

The proposed integrated policy is defined and modeled mathematically.

The paper focuses on finding simultaneously the optimal values of the preventive maintenance period, the buffer stock size, the sample size, the sampling interval and the control chart limits, such that the expected total cost per time unit is minimized.

The paper attempts to integrate in a single model the three main aspects of any manufacturing system: production, maintenance and quality. The considered system consists of one machine subject to a degradation process that directly affects the quality of products. The process and product quality control is carried out using an “x-bar” control chart. In the proposed model, a preventive maintenance action is performed every α inspections of product quality in order to reduce the shift rate to the “out-of-control” state. A corrective maintenance action is undertaken once the control limits are exceeded. In order to palliate perturbations caused by the stopping of the machine to undergo maintenance actions, a buffer stock is built up to ensure the continuous supply of the subsequent machine. The main goal of this work is to develop a model that captures the underlying link between the preventive maintenance policy, the buffer stock size and the parameters of an “x-bar” control chart used to control the quality of the product. Numerical experiments and a study of the effects of the input parameters variation on the obtained results are performed.

The existing models that simultaneously consider maintenance, inventory and control charts consist of a condition-based maintenance (CBM) policy. Periodic preventive maintenance (PM) has not been considered in such models. The proposed integrated model is original, in that it links production through buffer stocks, quality through a control chart and maintenance through periodic preventive maintenance (different practical settings and modeling approach than when CBM is used). Hence, this paper addresses practical situations where, for economic or technical reasons, only systematic periodic preventive maintenance is possible.

The purpose of this paper is to investigate the relationship between total productive maintenance (TPM) practices and operational performance (OP) in soft drinks manufacturing industry, Ethiopia.

In this study acceptability and implementation of five TPM practices (i.e., dependent factors: autonomous maintenance (AUT); safety, health and environment (SHE); education and training (EDT); focused improvement; and planned maintenance (PLM)) in soft drinks manufacturing industry have been elaborated to ascertain the benefits accrued as a result of successful TPM practices (i.e., independent variables) on OP (i.e., dependent variables). A self-administered survey seven-point Likert scale questionnaire was used for primary data collection. By using simple random sampling technique a total of 100 useable responses resulted in a 66.66 per cent response rate. Descriptive (mean, standard deviation) and inferential statistics (factor analysis, correlation, simple and multiple regression analysis) analysis were performed using Statistical Package for Social Sciences (SPSS) software (version-28) to identify the relationship and effect of TPM practices on OP. Five hypotheses were developed and tested.

Results show that four of the TPM practices were positively and significantly correlated with OP. Aggregate TPM shows positive and significant correlation with OP. Four hypotheses results revealed that the AUT; SHE; EDT and PLM practices have positive and significant relationship with OP and significantly improve OP. The results also show that the TPM practices have positive and significant relationship with OP and significantly improve cost effectiveness, product quality, on-time delivery and volume flexibility.

The benefits gained by TPM practices in selected soft drinks manufacturing industry have been highlighted, that could be genuine source of motivation to other companies to go in for TPM program. This research contributes to the literature by examining the contingency of various TPM enabling factors in the context of the Ethiopian soft drinks manufacturing sector, and it, therefore, provides direction to increase the success rate of TPM implementation. Study offers academics and practitioners a better understanding of the relationship and effect of the TPM practices on the OPs. Thus, practitioners will be able to make better and more effective decisions about the implementation of TPM practices for better OP results.

The relationship between the five factors TPM practices and OP has not yet been studied or reported in the case of soft drink manufacturing industry. The questionnaire manner and items developed, factor considered in this study, sampling method, deeply statistical data analysis techniques used, soft drink manufacturing industry, developing country like Ethiopia make this study unique and revealed the gap identification in this area. The study has contributed to the TPM literature with a better understanding of the five TPM practices and their association with a soft drink manufacturing industry OP that will provide valuable knowledge to top-management of manufacturing companies, to refine their current TPM practices and subsequently improve OP.

The traditional practice for maintenance, quality control and production scheduling is to plan independently irrespective of an interrelationship exist between them. The purpose of this paper is to develop an approach for integrating maintenance, quality control and production scheduling. The objective is to investigate the benefits of the integrated effect in terms of the expected total cost of system operation of the three functions.

The proposed approach is based on the conditional reliability of the components. Cost model for integrating selective maintenance, quality control using sampling-based procedure and production scheduling is developed using the conditional reliability. An integrated approach is such that, first an optimal schedule for the batches to be processed is obtained independently while the maintenance and quality control decisions are optimized considering the optimal schedule on the machine. The expected total cost of conventional approach, i.e. “No integration” is calculated to compare the effectiveness of integrated approach.

The integrated approach have shown a higher cost saving as compared to the independent planning approach. The approach is practical to implement as the results are obtained in a reasonable computational time.

The approach presented in this paper is generic and can be applied at planned as well as unplanned opportunities. The proposed integrated approach is dynamic in nature, as during maintenance opportunities, it is possible to optimize the decision on maintenance, quality control and production scheduling considering the current age of components and production requirement.

The originality of the paper is in the approach for integration of the three elements of shop floor operations that are usually treated separately and rarely touched upon by researchers in the literature.