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Maintenance Decision Making, Supported by Computerized Maintenance Management System
Volvo Group Trucks Operations Powertrain Production, Köping, Sweden .ORCID iD: 0000-0001-8729-2955
Western New England University, Springfield, MA, United States.
2016 (English)In: IEEE 2016 The Annual Reliability and Maintainability Symposium IEEE RAMS 2016, 2016Conference paper, Published paper (Refereed)
Abstract [en]

This paper is written based on the need for Computerized Maintenance Management System’s (CMMS) decision analysis capability to achieve world class status in maintenance management. Investigations indicate that decision analysis capability is often missing in existing CMMSs and collected data in the systems are not completely utilized. How to utilize the gathered data to provide guidelines for maintenance engineers and managers to make proper maintenance decisions has always been a crucial question. In order to provide decision support capability, the aim of this paper is to provide and examine three different decision making techniques which can be linked to CMMS and add value to collected data. This research has been conducted within a global project in a large manufacturing site in Sweden to provide a new maintenance management system for the company. The data from the main studies were collected through document analysis complemented by discussions with maintenance engineers and managers at the case company to verify the data. Methods including a Multiple Criteria Decision Making (MCDM) technique called TOPSIS, k-means clustering technique, and one decision making model borrowed from the literature were used. The results indicate the most appropriate maintenance decision for each of the selected machines/parts according to factors such as frequency of breakdowns, downtime, and cost of repairing. The paper concludes with a comparison of results obtained from the different decision making techniques and also a discussion on possible improvements needed to increase the capability of the maintenance decision making models.

Place, publisher, year, edition, pages
2016.
Keywords [en]
Computerized Maintenance Management System (CMMS), Maintenance Decision Making, Multiple Criteria Decision Making (MCDM), Data Clustering
National Category
Engineering and Technology Mechanical Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-32776DOI: 10.1109/RAMS.2016.7448086Scopus ID: 2-s2.0-84968884451ISBN: 978-1-5090-0248-1 (print)OAI: oai:DiVA.org:mdh-32776DiVA, id: diva2:1010090
Conference
IEEE 2016 The Annual Reliability and Maintainability Symposium IEEE RAMS 2016, 25 Jan 2016, Tucson, United States
Projects
Reducing maintenance-related wasteINNOFACTURE - innovative manufacturing developmentAvailable from: 2016-09-30 Created: 2016-08-24 Last updated: 2017-10-23Bibliographically approved
In thesis
1. Condition Based Maintenance in the Manufacturing Industry: From Strategy to Implementation
Open this publication in new window or tab >>Condition Based Maintenance in the Manufacturing Industry: From Strategy to Implementation
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The growth of global competition has led to remarkable changes in the way manufacturing companies operate. These changes have affected maintenance and made its role even more crucial for business success. To remain competitive, manufacturing companies must continuously increase the effectiveness and efficiency of their production processes. Furthermore, the introduction of lean manufacturing has increased concerns regarding equipment availability and, therefore, the demand for effective maintenance. That maintenance is becoming more important for the manufacturing industry is evident in current discussions on national industrialization agendas. Digitalization, the industrial internet of things (IoT) and their connections to sustainable production are identified as key enablers for increasing the number of jobs in industry. Agendas such as “Industry 4.0” in Germany and “Smart Industry” in Sweden are promoting the connection of physical items such as sensors, devices and enterprise assets, both to each other and to the internet. Machines, systems, manufactured parts and humans will be closely interlinked to collaborative actions. Every physical object will formulate a cyber-physical system (CPS), and it will constantly be linked to its digital fingerprint and to intensive connection with the surrounding CPSs of its on-going processes.

That said, despite the increasing demand for reliable production equipment, few manufacturing companies pursue the development of strategic maintenance. Moreover, traditional maintenance strategies, such as corrective maintenance, are no longer sufficient to satisfy industrial needs, such as reducing failures and degradations of manufacturing systems to the greatest possible extent. The concept of maintenance has evolved over the last few decades from a corrective approach (maintenance actions after a failure) to a preventive approach (maintenance actions to prevent the failure). Strategies and concepts such as condition based maintenance (CBM) have thus evolved to support this ideal outcome. CBM is a set of maintenance actions based on the real-time or near real-time assessment of equipment conditions, which is obtained from embedded sensors and/or external tests and measurements, taken by portable equipment and/or subjective condition monitoring. CBM is increasingly recognized as the most efficient strategy for performing maintenance in a wide variety of industries. However, the practical implementation of advanced maintenance technologies, such as CBM, is relatively limited in the manufacturing industry.

Based on the discussion above, the objective of this research is to provide frameworks and guidelines to support the development and implementation of condition based maintenance in manufacturing companies.  This thesis will begin with an overall analysis of maintenance management to identify factors needed to strategically manage production maintenance. It will continue with a focus on CBM to illustrate how CBM could be valued in manufacturing companies and what the influencing factors to implement CBM are. The data were collected through case studies, mainly at one major automotive manufacturing site in Sweden. The bulk of the data was collected during a pilot CBM implementation project. Following the findings from these efforts, a formulated maintenance strategy is developed and presented, and factors to evaluate CBM cost effectiveness are assessed. These factors indicate the benefits of CBM, mostly with regard to reducing the probability of experiencing maximal damage to production equipment and reducing production losses, particularly at high production volumes. Furthermore, a process of CBM implementation is presented. Some of the main elements in the process are the selection of the components to be monitored, the techniques and technologies for condition monitoring and their installation and, finally, the analysis of the results of condition monitoring. Furthermore, CBM of machine tools is presented and discussed in this thesis, focusing on the use of vibration monitoring technique to monitor the condition of machine tool spindle units.

Place, publisher, year, edition, pages
Eskilstuna: Mälardalen University, 2017
Series
Mälardalen University Press Dissertations, ISSN 1651-4238 ; 242
Keywords
Condition based maintenance; Condition monitoring; Manufacturing industry
National Category
Reliability and Maintenance
Research subject
Innovation and Design
Identifiers
urn:nbn:se:mdh:diva-37130 (URN)978-91-7485-355-1 (ISBN)
Public defence
2017-12-01, Raspen, Mälardalens högskola, Eskilstuna, 10:00
Opponent
Supervisors
Projects
INNOFACTURE - innovative manufacturing development
Available from: 2017-10-23 Created: 2017-10-23 Last updated: 2017-11-17Bibliographically approved

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