Multi-Objective Stochastic Optimization for Preventive Maintenance Planning

PresentationMaintenance is an essential part of mechanical integrity programs and aims to prevent the occurrence of process safety incidents and costly unplanned shutdowns. Maintenance can increase the reliability of equipment in productive systems and effective preventive maintenance programs enable maintenance activities to be planned proactively. However, maintenance planning is subject to resource scarcity and is rendered nontrivial due to system complexity, reliability model nonlinearity, and parametric uncertainty. Multi-objective stochastic mixed-integer nonlinear programming is well suited to addressing these challenges and is adopted here to optimize the time intervals in which to perform maintenance on different pieces of equipment. Following presentation of an optimal maintenance planning framework, a model is formulated and optimized accounting for: the effect of imperfect repair using an effective age model, equipment failure behavior using a Weibull reliability model, endogenous uncertainty in reliability model parameters, and the simultaneous need to satisfy the competing objectives of cost minimization and reliability maximization using the ε-constraint method. The results of the research consist of optimal maintenance plans, plots of resultant equipment and system reliability over time, and a Pareto frontier of optimal solutions from which the decision maker can select. The approach adopted here is illustrated with a case study and can be extended to improving the overall availability, effectiveness, and resilience of a variety of productive systems

a tailored maintenance management system to control spare parts life cycle

Abstract The maintenance of complex production systems became increasingly crucial to ensure the competitiveness of companies and service level to their clients. Because of product customization the number of mechanical and electrical components and functional groups of manufacturing lines enhanced with their complexity. To face this concern, the physical and logical design of such systems is typically partitioned among several groups of engineers and designers. Consequently, a holistic awareness of the whole project is lacking and the maintenance of such systems becomes even more challenging. In view of this, new tailored support-decision tools able to manage and control the life cycle of spare parts from their design, throughout the run time, and to their failure and replacement are necessary. This paper illustrates an original maintenance management system (MMS) resulting by the combination of different computerized tools able to integrate the information flow behind the life cycle of a generic component. The proposed system supports coordination among groups of engineers and practitioners through graphic user interfaces (GUIs) and performance i.e. cost, reliability, dashboards, which lead decision-making from the design phase to the planning of maintenance tasks along the life of the manufacturing line. These tools are validated with a real-world instance from the tobacco industry which allows assessing how components belonging to the same functional group may differently behave over their life cycle. The results suggest that the holistic awareness on the whole manufacturing system provided by the proposed MMS can support task design and schedule of maintenance actions providing the reduction of more than 20% of the total cost and time for maintenance actions. The practical example shown contributes to shed light on the potentials of new paradigms for maintenance management in the industry 4.0

Criticality evaluation to support maintenance management of manufacturing systems

This paper focuses on criticality evaluation for supporting daily equipment maintenance management and the definition of medium and long-term maintenance actions to improve equipment and, therefore, productivity. These two different purposes led to the development of two different methods for criticality evaluation, using criteria adjusted for each case. The first method is based on rules for defining priorities for corrective and preventive maintenance tasks. Since a failure mode of critical equipment is not necessarily critical, priorities for maintenance tasks are assigned to tasks rather than to equipment. The second method uses Analytic Hierarchy Process to prioritize equipment based on its performance. This method is based on the indicators commonly monitored by maintenance departments. In addition to assessing equipment performance, it considers the maintenance effort made to achieve the evaluated performance. The selection of the criticality criteria and the development of the methods was based on literature review and triggered by a case study in a multinational automotive company. With the integration of the proposed methods in a computerized maintenance management system, maintenance technicians and managers are able to know in real time the tasks that should be performed first and to monitor the overall performance of equipment in the plant, focusing improvements where they are more required.POFC - Programa Operacional Temático Factores de Competitividade (UID/CEC/00319/2013

Service-Oriented Computing for intelligent train maintenance

The purpose of this work is to apply the servicization of enterprise information systems in maintenance, particularly in the management of the maintenance process of the component parts of trains. Service Oriented Architecture (SOA) is an architectural approach that permits servicization since it provides a flexible set of design principles used during the modeling practices (abstraction and realization). With a view to supporting the model-driven engineering of software systems, Mode Driven Architecture (MDA) is a design approach delivering a set of guidelines for the configuring of specifications in systems development. Therefore, the combination of these two approaches can be fruitful to address the challenging issues the enterprise information system is facing today. Our study is based on a methodological approach using the MDA models for the automatic generation of web service. The case study concerns a Railways Maintenance Workshop (RMW) at Sidi Bel Abbes (Algeria). Finally, the information system for the management of maintenance of the component parts of passengers and baggage railcars, using the generated solution, is realized and deployed. This software helps to have better management of the RMW by the effective planning of interventions, improve performance by increasing reliability, traceability, and availability of the equipment (parts)

The scheduling of maintenance. A resource-constraints mixed integer linear programming model

The scheduling of preventive maintenance is crucial in reliability and maintenance engineering. Hundreds of parts compose complex machines that require replacement and/or repairing. Maintenance involves the machine vendor (1), the machine user (2) and the service maintenance provider (3). The vendor and the maintenance service provider have to guarantee a high level of availability and productivity of the machines and maintain their down-time at a minimum even though they are installed worldwide and usually far from the vendor\u2019s headquarters and/or the locations of the provider\u2019s regional service offices. Moreover, many companies have great profits from maintenance and spare parts management. This study aims to illustrate an original mixed integer linear programming (MILP) model for the cost-based, reliability-based and resource-constraints scheduling of preventive maintenance actions. The model minimizes the total cost function made of spare parts contributions, the cost of the execution of the preventive actions and the cost of the additional repair activity in case of unplanned failure. The cost of the personnel of the producer and/or the maintenance service provider is also included. Finally, the paper presents a case study in a what-if environment demonstrating the effectiveness and the novelty of this study in real and complex applications

Generator maintenance scheduling

Διπλωματική εργασία--Πανεπιστήμιο Μακεδονίας, Θεσσαλονίκη, 2019.The ongoing Electricity markets restructuring on a global scale, shifted much attention from centralized and in particular small isolated systems, typically found in islands. It is true that such systems, mainly run on liquid fuel Gensets, if not interconnected to some major grid may ever exhibit investment interest. As a result, many utilities constantly struggle while others due to fuel cost and the ever-increasing emission control restrictions, are near the verge to collapse. It is this necessity that actually urges for optimal managerial practices to exploit the last penny spent until-if ever, all these resource guzzling Gensets reach their retirement age. In this thesis we respect a realistic power plant feeding the tourist industry of an island. A 0/1 MILP formulation enables to accurately account for operation, maintenance and reliability status cost, providing in practical time a palette full of decision options. System demand is allocated in classes whereas the overall proposed reliability approach renders any chosen optimal schedule easily implemented in practice