About: Monitoring Maintenance Lifecycle is a research topic. Over the lifetime, 352 publications have been published within this topic receiving 6174 citations.
TL;DR: In this paper, the authors present a review of current Paradigms and Practices of applied maintenance models and apply them to real-world manufacturing systems. But they do not consider the impact of human error in maintenance.
Abstract: Maintenance Organization.- Maintenance Productivity and Performance Management.- Failure Statistics.- Failure Mode and Effect Analysis.- Maintenance Control.- Guidelines for Budgeting and Costing Planned Maintenance Services.- Simulation Based Approaches for Maintenance Strategies Optimization.- Maintenance Forecasting and Capacity Planning.- Integrated Spare Parts Management.- Turnaround Maintenance.- Maintenance Planning and Scheduling.- Models for Production and Maintenance Planning in Stochastic Manufacturing Systems.- Inspection Strategies for Randomly Failing Systems.- System Health Monitoring and Prognostics - A Review of Current Paradigms and Practices.- Applied Maintenance Models.- Reliability Centered Maintenance.- Total Productive Maintenance.- Warranty and Maintenance.- Delay Time Modeling for Optimized Inspection Intervals of Production Plant.- Integrated e-maintenance and Intelligent Maintenance Systems.- Maintainability & System Effectiveness.- Safety and Maintenance.- Maintenance Quality and Environmental Performance Improvement: An Integrated Approach.- Industrial Asset Maintenance and Sustainability Performance: Economic, Environmental, and Societal Implications.- Human Reliability and Error in Maintenance.- Human Error in Maintenance - A Design Perspective.
TL;DR: The use of PLM processes and tools to manage product data effi ciently, with increased visibility and control over the life cycle of the product, is expanding.
Abstract: Manufacturers are faced with many challenges, such as globalization, disparate enterprise systems and a lack of platform maturity. These will only multiply as technology advances, offshore manufacturing increases and new ways of working emerge. To overcome these challenges, many manufacturers have embraced product lifecycle management (PLM) or have expanded the use of PLM processes and tools to manage product data effi ciently, with increased visibility and control over the life cycle of the product.
TL;DR: A conceptual framework that provide guidelines for choosing maintenance function performance indicators is proposed and seeks to align maintenance objectives with manufacturing and corporate objectives, and provides a link between the maintenance objectives, maintenance process/efforts and maintenance results.
TL;DR: The Maintenance Management Framework as discussed by the authors describes and reviews the concept, process and framework of modern maintenance management of complex systems focusing specifically on modern modelling tools (deterministic and empirical) for maintenance planning and scheduling.
Abstract: The Maintenance Management Frameworkdescribes and reviews the concept, process and framework of modern maintenance management of complex systems; concentrating specifically on modern modelling tools (deterministic and empirical) for maintenance planning and scheduling. It presents a new perspective of maintenance management by: focusing on the course of maintenance actions; presenting a structure that ensures proper support for current maintenance managers; clarifying the functionality that is required from information technology when applied to maintenance and the functions of modern maintenance engineering; and creating a set of practical models for maintenance management planning and scheduling. The discussion of all of these issues is supported through the use of case studies. The Maintenance Management Frameworkwill be beneficial for engineers and professionals involved in: maintenance management, maintenance engineering, operations management, quality, etc. It will also be of interest to graduate students and researchers in this field.
TL;DR: Foundations and technologies required for continuous maintenance within the Industry 4.0 context are presented and the role of IoT, standards and cyber security are identified.
Abstract: High value and long life products require continuous maintenance throughout their life cycle to achieve required performance with optimum through-life cost. This paper presents foundations and technologies required to offer the maintenance service. Component and system level degradation science, assessment and modelling along with life cycle ‘big data’ analytics are the two most important knowledge and skill base required for the continuous maintenance. Advanced computing and visualisation technologies will improve efficiency of the maintenance and reduce through-life cost of the product. Future of continuous maintenance within the Industry 4.0 context also identifies the role of IoT, standards and cyber security.