Manufacturing-error-based maintenance for high-precision machine tools

Nowadays, the condition-based maintenance (CBM), in which repairs are triggered by the heuristic symptoms of the component faults, is finding increasing applications in the industrial fields. However, for the high-precision machine tools, the conventional CBM might not be the optimal option, which is uneconomic and incapable of ensuring their machining accuracy. In order to overcome these shortcomings, this paper propose the manufacturing-error-based maintenance (MEBM), where the repairs are initiated based on the manufacturing errors instead of the heuristic symptoms. In MEBM, repairs are taken properly at the occurrence of the excessive machining errors, and therefore, the premature and redundant maintenance can be avoided and the maintenance cost can be minimized; what is more, the machining errors are controlled in the closed loops, and therefore, the machining accuracy can be guaranteed. Based on the principles of the MEBM, a prototype maintenance system—the transient backlash error (TBE)-based maintenance system—is established. To achieve this aim, first, the width of the backlash in the mechanical chain is measured by utilizing the built-in encoders and the analytical mapping relationship between the backlash width and the TBE is derived. Relying on these foundations, the TBE can be indirectly estimated. Then, the warning threshold of the TBE is customized according to the permissible roundness error of the workpiece. Thus, the maintenance actions can be precisely implemented: when the monitored TBE exceeds its warning threshold, maintenance workers will be notified to lessen the backlash width, and meanwhile, the permissible maximal size for the backlash will also be informed

A STEPPING STONE TOWARDS KNOWLEDGE BASED MAINTENANCE

Maintenance decision making becomes more and more a management concern. Some decades ago, maintenance was still often considered as an unavoidable side effect of production. The perception of maintenance has evolved considerably. One of the current issues is the maintenance concept, being the mix of maintenance interventions and the general framework for determining this mix. In this paper we describe a modular framework, called Knowledge Based Maintenance, for developing a customised maintenance concept. After describing the general framework and its decision support use, some case experiences are given. This experience covers some elements of the proposed framework

The development of a maintenance gap analysis tool for use within the automotive supply chain: A case study perspective

Automotive manufacture contributed £82 billion to the UK Economy in 2017. In addition, the production of vehicles within the UK continues to rise, with 1.65 million vehicles produced in 2017. Lean production methods, compounded by synchronous delivery to an Original Equipment Manufacturer (OEM), ensure membership of the automotive supply chain is challenging. To meet this challenge, participants in manufacturing operations within any business must operate both effectively and efficiently. Interestingly, despite the apparent success of the industry, research has revealed that disjointed maintenance practice within the supply chain is evident and augmenting a difficult production environment. This research gathered empirical data from four case study partners who operate at Tier 1 within the automotive supply chain. The findings demonstrate the majority of research partici-pants operate with an underperforming maintenance department due to a number of barriers and constraints. A worrying consequence of poor maintenance execution and an unsupportive maintenance culture has also emerged. To mitigate the risk of poor maintenance performance, manufacturers are retaining excessive safety stock to ensure delivery targets are met. As well as establishing constraints preventing maintenance performance, areas of best practice have been highlighted, with both characteristics integrated into a Gap Analysis Tool. This paper will discuss the development and subsequent testing of the Gap Analysis Tool with one case study participant and the potential impact for a manufacturer within the automotive supply chain

On the Advancement of Maintenance Management Towards Smart Maintenance in Manufacturing

The purpose of this work is to envision the future of maintenance without forgetting the past and present of maintenance practices. Indeed, there is a big potential for maintenance, fostered by the promises of the Fourth Indus-trial Revolution. At the same time, there is still a widespread evidence of the state of practices leading to assert that maintenance is not yet advanced as it would be expected. Thus, comparing the vision supported by advanced maintenance systems, through the concepts of E-maintenance, Internet of Things and Cyber Physical Systems, with the evidences on the state of prac-tices collected based on a sample of more than 300 industrial plants, we come up with a reflection on the advancement of maintenance management towards Smart Maintenance

Understanding Maintenance Decisions: How to Support Acquisition of Capital Assets

This chapter contributes with theoretical and practical insights on maintenance decision making during acquisition of capital assets. We give theoretical insights about maintenance decision making by reviewing the literature, while our practical insights come from examples of the decisions made at a maintenance organization for rolling stock: NedTrain. We find that strategic maintenance decisions are more relevant before contracting than tactical or operational decisions, and they have the largest potential to impact Life Cycle Costs. The research on strategic maintenance decisions is too broad to review individual decisions, and therefore we review papers that structure decisions in the form of frameworks. We find that according to the literature, assets and their maintenance services should be developed concurrently. However, we find in practice that NedTrain’s approach is to fit new assets into the existing maintenance services, while there are parallel continuous improvement processes for those services. From practice, we conclude that strategic maintenance decisions are not concurrent to rolling stock design decisions. We also conclude that there is a need for methods and tools to support strategic maintenance decision making during early stages of acquisition, especially before contracting