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Manufacturing organizations are continuously in the mode of identifying and implementing mechanisms to achieve a competitive edge. To this point manufacturers have recognized the critical role of equipment in the productivity of manufacturing operations. With the current trend of manufacturers attempting to lean out their production processes, primary and auxiliary equipment have become even more important to manufacturers as measured by productivity, quality, delivery, and cost metrics. As a result of the focus on lean manufacturing, maintenance management has found a new vigor and purpose to increase equipment capacity and capability. However, the most proactive maintenance strategy is not always the most effective utilization of resources. It is typical for manufacturers to integrate both reactive and proactive maintenance to define a cost effective maintenance strategy. A simulation-based approach is presented that allows an end user to develop such a maintenance strategy.
Recent developments in reliability engineering has become the most challenging and demanding area of research. Modeling and Simulation, along with System Reliability Engineering has become a greater issue because of high-tech industrial processes, using more complex systems today. This book gives the latest research advances in the field of modeling and simulation, based on analysis in engineering sciences. Features Focuses on the latest research in modeling and simulation based analysis in reliability engineering. Covers performance evaluation of complex engineering systems Identifies and fills the gaps of knowledge pertaining to engineering applications Provides insights on an international and transnational scale Modeling and Simulation Based Analysis in Reliability Engineering aims at providing a reference for applications of mathematics in engineering, offering a theoretical sound background with adequate case studies, and will be of interest to researchers, practitioners, and academics.
To be able to compete successfully both at national and international levels, production systems and equipment must perform at levels not even thinkable a decade ago. Requirements for increased product quality, reduced throughput time and enhanced operating effectiveness within a rapidly changing customer demand environment continue to demand a high maintenance performance. In some cases, maintenance is required to increase operational effectiveness and revenues and customer satisfaction while reducing capital, operating and support costs. This may be the largest challenge facing production enterprises these days. For this, maintenance strategy is required to be aligned with the production logistics and also to keep updated with the current best practices. Maintenance has become a multidisciplinary activity and one may come across situations in which maintenance is the responsibility of people whose training is not engineering. This handbook aims to assist at different levels of understanding whether the manager is an engineer, a production manager, an experienced maintenance practitioner or a beginner. Topics selected to be included in this handbook cover a wide range of issues in the area of maintenance management and engineering to cater for all those interested in maintenance whether practitioners or researchers. This handbook is divided into 6 parts and contains 26 chapters covering a wide range of topics related to maintenance management and engineering.
This volume contains the papers presented at IALCCE2018, the Sixth International Symposium on Life-Cycle Civil Engineering (IALCCE2018), held in Ghent, Belgium, October 28-31, 2018. It consists of a book of extended abstracts and a USB device with full papers including the Fazlur R. Khan lecture, 8 keynote lectures, and 390 technical papers from all over the world. Contributions relate to design, inspection, assessment, maintenance or optimization in the framework of life-cycle analysis of civil engineering structures and infrastructure systems. Life-cycle aspects that are developed and discussed range from structural safety and durability to sustainability, serviceability, robustness and resilience. Applications relate to buildings, bridges and viaducts, highways and runways, tunnels and underground structures, off-shore and marine structures, dams and hydraulic structures, prefabricated design, infrastructure systems, etc. During the IALCCE2018 conference a particular focus is put on the cross-fertilization between different sub-areas of expertise and the development of an overall vision for life-cycle analysis in civil engineering. The aim of the editors is to provide a valuable source of cutting edge information for anyone interested in life-cycle analysis and assessment in civil engineering, including researchers, practising engineers, consultants, contractors, decision makers and representatives from local authorities.
Safety and Reliability – Theory and Applications contains the contributions presented at the 27th European Safety and Reliability Conference (ESREL 2017, Portorož, Slovenia, June 18-22, 2017). The book covers a wide range of topics, including: • Accident and Incident modelling • Economic Analysis in Risk Management • Foundational Issues in Risk Assessment and Management • Human Factors and Human Reliability • Maintenance Modeling and Applications • Mathematical Methods in Reliability and Safety • Prognostics and System Health Management • Resilience Engineering • Risk Assessment • Risk Management • Simulation for Safety and Reliability Analysis • Structural Reliability • System Reliability, and • Uncertainty Analysis. Selected special sessions include contributions on: the Marie Skłodowska-Curie innovative training network in structural safety; risk approaches in insurance and fi nance sectors; dynamic reliability and probabilistic safety assessment; Bayesian and statistical methods, reliability data and testing; oganizational factors and safety culture; software reliability and safety; probabilistic methods applied to power systems; socio-technical-economic systems; advanced safety assessment methodologies: extended Probabilistic Safety Assessment; reliability; availability; maintainability and safety in railways: theory & practice; big data risk analysis and management, and model-based reliability and safety engineering. Safety and Reliability – Theory and Applications will be of interest to professionals and academics working in a wide range of industrial and governmental sectors including: Aeronautics and Aerospace, Automotive Engineering, Civil Engineering, Electrical and Electronic Engineering, Energy Production and Distribution, Environmental Engineering, Information Technology and Telecommunications, Critical Infrastructures, Insurance and Finance, Manufacturing, Marine Industry, Mechanical Engineering, Natural Hazards, Nuclear Engineering, Offshore Oil and Gas, Security and Protection, Transportation, and Policy Making.
Devising optimal strategy for maintaining industrial plant can be a difficult task of daunting complexity. This book aims to provide the plant engineer with a comprehensive approach for tackling this problem, that is, for deciding maintenance objectives, formulating equipment life plans and plant maintenance schedules, and others.
Maintenance serves a critical role in manufacturing systems by ensuring that machines and other assets remain in a productive working condition. The primary objective of maintenance optimization is to determine when to conduct maintenance and which machines should be maintained. Recent advances in industrial maintenance have sought to use online information obtained from sources such as machine sensors and manufacturing execution system software to provide real-time decision support. Such predictive maintenance strategies combine abundant online manufacturing data with techniques in simulation, planning, and artificial intelligence to make effective maintenance decisions and support the overall performance of the system. In this dissertation we examine several challenges associated with adopting real-time maintenance decision support in complex manufacturing systems. One such challenge is that of modeling complex machine configurations that are often found in modern manufacturing systems. It can be difficult or impossible to model the behavior of these systems analytically without imposing unrealistic simplifying assumptions. One of the goals of this work is therefore to propose a method of maintenance optimization and planning that is generalizable to arbitrarily configured systems. We also introduce a discrete-event simulation package that has been developed as a part of this work and is capable of modeling these systems of interest. Additionally, real-world manufacturing systems are typically subject to constraints on available maintenance resources which limits the number of maintenance jobs that may be conducted simultaneously. In these settings, the maintenance planner must determine how to prioritize competing maintenance activities and allocate these limited resources throughout the system. This work addresses these challenges by proposing a simulation-based maintenance optimization and planning approach to seek an optimal maintenance policy and prioritize maintenance in complex systems. We formulate condition-based maintenance policy optimization as a discrete optimization via simulation problem and seek a solution using the Gaussian Markov Improvement Algorithm and a genetic algorithm. The result is a degradation threshold for each machine in the system that determines when a machine should request maintenance. To overcome the problem of capacity-constrained maintenance resources, we first propose a dynamic priority scheduling heuristic that aims to minimize throughput disruption due to downtime for maintenance. We then improve upon this scheduling heuristic by employing a reinforcement learning approach to seek the best maintenance action in each state of the system. We use Monte Carlo tree search to progressively build a search tree within the system state space and evaluate alternative sequences of actions in order to find that which maximizes the expected reward. We demonstrate that our proposed method of online prioritization results in improved system-level performance when compared to commonly used maintenance prioritization methods. Furthermore, we apply a case-based reasoning framework to retain and reuse relevant experience that improves the decision-making efficiency over time. In addition to improved system productivity, the proposed approach results in reduced time needed to identify optimal maintenance actions which is particularly important when critical maintenance decisions must be made quickly.
Over the last decades maintenance management has evolved from a somewhat neglected function into a full-fledged business function in the industry as well as in the service sector.This book provides a structured approach to maintenance management. It covers maintenance strategy decisions, resource management, assessment system design, etc. Decision support models and tools in these areas are discussed from the theoretical point of view and illustrated by numerous examples and case studies.Due to its concept the book can be interesting for students as well as practitioners.This book is the successor of Maintenance Management (2000), which gave an introduction in the field.