https://www.mdu.se/

The goal of this research is to identify and classify factors creating maintenance-related waste. A workshop study has been performed in order to identify root-causes for maintenance-related waste. In total, 16 categories were found in the analysis and it is concluded that these are heavily reliant on human factors as a root- or major contributory cause. These, together with factors based on a literature review have been incorporated into a classification model. The model can be used in creating awareness in, as well as provide a basic framework for decision making of, which waste to target for elimination.

The reduction and elimination of maintenance-related waste is receiving increasing attention because of the negative effect of such waste on production costs. The overall goal of this research is to identify and prioritize factors that can be considered maintenance-related waste within the automotive manufacturing industry. Five manufacturing companies participated in a workshop to identify root causes of maintenance-related waste; 16 categories were found. The identified factors were heavily reliant on human factors as a root or major contributory cause at different levels affecting performance and productivity. For prioritization, the evidential reasoning (ER) approach which is one of the latest developments in multi-criteria decision-making is applied. A basic tree structure necessary for ER assessment is developed based on the workshop results as well as literature on human factors. Then, a survey on basic attributes at the lowest level of this tree is designed and performed at one of the companies participating in the workshop. The application of ER shows that, on an overall level, "management condition" is in first order and "maintainer condition" and "working condition" are in second and third order respectively as the worst cases for creating maintenance-related waste. On the most delimited level "inadequate resources" and "weather/indoor climate" have the highest and lowest average scores respectively in ER ranking or prioritization. This methodology with its resulting ranking can be used as a tool to create awareness for managers seeking to reduce or eliminate maintenance-related waste.

Proactive maintenance management of world-class standard is close to impossible without the support of a computerized management system. In order to reduce failures, and failure recurrence, the key information to log are failure causes. However, Computerized Maintenance Management System (CMMS) seems to be scarcely used for analysis for improvement initiatives. One part of this is due to the fact that many CMMS utilizes free-text fields which may be difficult to analyze statistically. The aim of this study is to apply Natural Language Processing (NPL), Ontology and Machine Learning (ML) as a means to analyze free-textual information from a CMMS. Through the initial steps of the study, it was concluded though that none of these methods were able to find any suitable hidden patterns with high-performance accuracy that could be related to recurring failures and their root causes. The main reason behind that was that the free-textual information was too unstructured, in terms of for instance: spelling- and grammar mistakes and use of slang. That is the quality of the data are not suitable for the analysis. However, several improvement potentials in reporting and to develop the CMMS further could be provided to the company so that they in the future more easily will be able to analyze its maintenance data.

The purpose of the study is to describe an information theory in order to achieve a fruitful discussion of information within condition monitoring in a condition based maintenance context. The paper is based on a qualitative and interdisciplinary approach. A case study is performed at four Swedish paper mills and one condition monitoring supplier. Interviews have been the main method for data collection; however, observations and studies of artifacts are included in the study also. The main contribution of the study is a framework that visualizes how data and five different forms of information interact and turns into knowledge about a machine’s condition. These forms of information are all necessary to take into consideration when implementing and operating a condition based maintenance program. The research results state that it is relevant to allow and encourage the technicians and operators to utilize several forms of information when assessing the condition of an asset, and, thus, to not put too much trust in the condition monitoring technology alone. Also, it can be important to encourage user interface designers to reflect upon the different contexts and information forms as they design information in a condition monitoring interface.

In order for factories to stay competitive in the current open global market, there should be efforts to put on optimizing the value stream of producing goods. Within this context, Industrial Internet of Things (IIoT) has been emerged as a technology aiming at achieving high productivity performance in manufacturing. A smart manufacturing approach also requires a smart maintenance management as it plays a crucial role in securing the productivity. IIoT applications are traditionally completed by the cloud computing technology to serve the required services. In this paper, we argue that maintenance processes have requirements that cannot be accomplished by solely the cloud computing technology. We identify several of these requirements. Then, we propose a platform using the fog computing technology, as a recently raised technology in IIoT, to enhance the smart maintenance management. We also discuss the ability of the platform in fulfilling the identified requirements.

Maintenance, as a form of production support, has become increasingly important to ensure equipment availability, quality products, on-time deliveries, and plant safety. Condition based maintenance, where it fits, is one maintenance solution that can increase the effectiveness of maintenance execution. Condition based maintenance is though not utilized in Swedish industry to the extent one would have expected. One reason for this is a gap between theory and practice when it comes to implementing and operating a condition based maintenance approach. Therefore, the purpose of this paper is to investigate how a condition based maintenance approach can be implemented in an industrial setting, and to develop a method that can assist companies in their implementation efforts. The conclusions can be summarized as follows: implementing condition based maintenance consists of many general enabling factors, and it is highly important to consider the interplay between technology, humans, and the organization, rather than just focusing on technology.

Som ett led i forskningsprojektet ”Tillståndsbaserat underhåll i tekniska system2 ” genomfördes en enkät för att ta reda på i vilken utsträckning olika företag och industrier/branscher använder sig av tillståndsbaserat underhåll. Enkäten bestod av 10 stycken frågor med olika svarskategorier (se Metod och Bilaga). Syftet med enkäten var att snabbt få en bild av hur svensk industri utför sina underhållsaktiviteter. Total samlades 28 ifyllda enkäter in. För att underlätta sammanställning delades enkätsvaren in i fyra kategorier av industrier: process-, verkstads-, läkemedels/livsmedels- och energiindustrin. Resultatet ur en sådan här liten undersökning behöver naturligtvis inte vara representativt för hela den svenska industrin, dock kan vissa slutsatser dras.

One practical solution in prioritizing which maintenance improvement initiative to undertake is by using Pareto analysis. This has also been advocated for, as one tool (of many), to use within maintenance by many maintenance research practitioners. However, there are some drawbacks and potential sources of errors if not being cautious. The main objective of this research is to develop and test a tool to be utilized for prioritization purposes of maintenance improvement initiatives. The purpose of the paper is to exemplify, from an industrial case, some of the strengths and weaknesses of this approach.

The objective of this paper is to present the process, results, and range of usability of a machine classification in a company that is producing discrete items. The classifications were built on the four factors of: (1) if the machines had any redundancy, (2) the utilization factor of the machines, (3) the quality impact of the machines, and finally, (4) the age of the machines. Through different levels and an assessment process the machines were classified in AAA-, AA-, A-, B-, or C-classes, AAA being the most critical. The classifications were performed in teams consisting of representatives from maintenance- and production engineering as well as production managers and operators, this, in order to achieve a consensus regarding the classification results. The result not only gave a deepened view on the factory layout, it also gave a good foundation to prioritize many improvement initiatives. Several ranges of use will be illustrated in the paper, as well as how the process and results has been received by the employees.

Today, the Swedish industry is budgeting billions in maintenance related costs on a yearly basis. The high costs come from productivity losses due to low availability. With condition based maintenance the maintenance intervals will be a lot more dynamic and no actions will be done unnecessarily. Sensor technology makes it possible to monitor an assets most important components. Different Artificial Intelligence techniques make it possible to analyze the measured data. With process knowledge of the monitored asset the analysis will show whether maintenance actions need to be performed or not. The condition based maintenance approach has been tried successfully on different engineering industries; now, the time has come to rail vehicles.

Examining the standards and standardization proposals within the Condition Based Maintenance (CBM) technology and specific within CBM systems, conclusions might be drawn as to where the technical development are or perhaps should be heading. Reviewing the standardization proposals promoted by the organizations of MIMOSA and OSA-CBM and the published standards IEEE Std 1451, IEEE Std 1232, and ISO 13373-1 it can be concluded that the future technical development might or should be heading towards prognostication and calculations of remaining useful life.

The objective with this paper is to study possible methods and tools to be used in a decision and development support model when implementing condition monitoring tools as a part of implementing a condition based maintenance strategy. The paper shortly discusses the condition based maintenance strategy, Six Sigma, Systems Engineering, and a synopsis of the former three topics. The result presented in this paper is a proposed model possible to use when performing process improvement projects, specifically within the framework of maintenance strategies and condition based maintenance in particular. The model is primarily to be used to decide if condition based maintenance really is the correct process improvement to initiate, if so on what assets in particular, and later also support the choice of which technology or technologies to utilize. The model draws from theory on the DMAIC methodology and the V-diagram model but also incorporates several tools and measurements, such as: failure mode and effect analysis, fault tree analysis, OEE- and DuPont-calculations, organizational maturity level estimation etc.

During implementation of a condition based maintenance approach numerous decisions lie ahead. A number of factors need to be taken into consideration in the decision-making. This paper, based upon theory and a brainstorming session, suggest a decision-making guideline. The suggested guideline covers the steps of; feasibility test, assignment of responsibilities, selection of assets to monitor, selection of parameters and techniques, and selection of technologies, in order to manage the decision-making more structured during implementation of condition based maintenance.

The objective with this paper is to present ideas, views, and experiences to form general guidelines for a condition based maintenance (CBM) implementation model. Empirics on the topic have been gathered through E-mail questions to a group of professionals within the Swedish maintenance field. Ideas, views, and personal experiences of the respondents are presented, compared, and analyzed. 14 factors were distinguished as important to take in consideration when implementing CBM. The most interesting finding though might be found in the aspect of a relative common ground that the respondents from the different groups have provided in their answers. It thus seems that it might be possible to develop a general implementation model for condition monitoring (CM) tools and the CBM strategy, at least more strategic guidelines. A first draft of such guidelines is presented in the result section of the paper.

The preventive maintenance strategy condition based maintenance has been reported to hold many advantages compared to predetermined and corrective maintenance. Although, investigation shows that the condition based maintenance strategy is not utilized in the Swedish industry to the extent one might expect. This paper sets out that the issue can be inherent from an organizational point of view and that general guidelines and implementation models of condition based maintenance thus far has been absent. The objective with this paper is to present ideas, views, and experiences to form general guidelines for a condition based maintenance implementation model. Empirics on the topic have been gathered through E-mail questions to a group of professionals within the Swedish maintenance field. Four groups of professionals: they who have implemented condition monitoring on their production process, they who have implemented condition monitoring into their products, they who teach within the area of maintenance, and they who develop condition monitoring tools, give their views on some open questions. Ideas, views, and personal experiences of the respondents are presented, compared, and analyzed. 14 factors were distinguished, including e.g.: management support, cooperation between departments, to quantify gains and losses, to visualize incentives etc., as important to take in great consideration when implementing condition based maintenance. The most interesting finding though might be found in the aspect of a relatively common ground that the respondents from the different groups have provided in their answers. It thus seems that it might be possible to develop a general implementation model for condition monitoring tools and the condition based maintenance strategy, at least more strategic guidelines. The discussion in the paper provides a first draft of such guidelines focusing on qualitative and some quantitative activities to be performed in three phases of an implementation process: namely before, in designing, and during the actual implementation.

The purpose of this paper is to present ideas, views, and experiences on how to communicate and motivate the benefits in introducing condition based maintenance in a discrete item manufacturing organization. The paper is built on two years of participant-observation in an industrial context.

In order to stay competitive, it is necessary for companies to continuously increase the effectiveness and efficiency of their production processes. High availability has, thus, increased in importance. Therefore, maintenance has gained in importance as a support function for ensuring, e.g., quality products and on-time deliveries. Maintenance, though, is a costly support function. It has been reported that as much as 70% of the total production cost can be spent on maintenance. Further, as much as one-third of the cost of maintenance is incurred unnecessarily due to bad planning, overtime cost, limited or misused preventive maintenance, and so on. In so, condition based maintenance is introduced as one solution for a more effective maintenance.

In condition based maintenance, critical item characteristics are monitored in order to gain early indications of an incipient failure. Research, though, has shown that condition based maintenance has not been implemented on a wide basis. Therefore, the purpose of this research is to investigate how a condition based maintenance approach can be implemented in an industrial setting, and to develop a method that can assist companies in their implementation efforts. Further, the research has been divided in three research questions. They focus on: constituents of a condition based maintenance approach, decision-making prior implementation of condition based maintenance, and finally, the implementation of condition based maintenance in a company.

By using a systems approach and a case study process, how condition based maintenance can be implemented as a routine has been investigated. The result is an implementation method in which four suggested phases are presented. The method starts with a feasibility test. It then continues with an analysis phase, an implementation phase, and an assessment phase. The conclusions can be summarized as follows: implementing condition based maintenance consists of many general enabling factors, including management support, education and training, good communication, and motivation etc.

Swedish industries maintenance-related costs run into billions on a yearly basis. Research has shown that up to 20% of the costs go to waste in non-realized revenue due to poor maintenance decisions. Both excessive and lacking maintenance can be harmful to an asset. A technology that strives to make the right judgements in maintenance intervals is the Condition Based Maintenance (CBM) technology. During the last decade the development in CBM technology has increased rapidly. A variety of different products can be found on the market. However developments are, in many cases, directed to specific applications and the results of a prototype are not always generally reproducible. One way to direct development in CBM technology to more general solutions can be to follow standards and standardization proposals. Within the technology, two standards and two standardization proposals can be found. IEEE 1451 and IEEE 1232, MIMOSA and OSA-CBM have been found to be the most interesting standards that lie within the scope of the CBM technology.

This article presents two case studies and theory on the topic of implementing a condition based maintenance approach. It visualizes that condition based maintenance, within the Swedish industry, is utilized to a lesser degree than corrective and predetermined maintenance, and argues that one reason for this is the difficulty in implementation. It also argues that additional factors, beyond technical aspects within the condition based maintenance approach, are necessary to take into consideration if successful implementation is to be achieved. The purpose of the two case studies was to investigate the process of implementing a condition based maintenance approach. The result of the investigation was compiled into a checklist with important factors to take into consideration when attempting to implement condition based maintenance within an industrial setting.

Rapporten har som mal att presentera en undersokning om fordelar med att implementera tillstandsovervakning och tillstandsbaserat underhall pa Stridsvagn 122. Undersokningen avgransades till slutvaxeln. Rekommendationer efter arbetet kan sammanfattas som att implementera tillstandsovervakning pa slutvaxeln inte ar applicerbart utifran ekonomiska, sakerhets- och tillganglighetsaspekter, da fordelarna antagligen inte skulle overstiga investeringskostnaden. Tillstandsbaserat underhall bor dock inte helt overges av FMV for Stridsvagn 122 da overvakning av andra delsystem skulle kunna ge stora fordelar.

Purpose – The purpose of this paper is to develop a novel training material for the performance indicator overall equipment effectiveness (OEE) in the form of a game-based learning (GBL) approach to be used in Industry and University context. The paper will present the development of the game as well as results from tests of the game with Industry employees and University students. Design/methodology/approach – The data that are used in the game have been acquired from real OEE data logs of a reference company. The game has been refined iteratively using feedback from the participants of the tests. Findings – The paper presents the game with its components and learning objectives. A comparison of various theoretical factors on GBL and the novel trainingmaterial is performed and future improvements are suggested. Research limitations/implications – The game has been developed based on OEE data logs from only one reference company. Practical implications – The training material and specifically the game can be used to train Industrial workers and University students to better envision OEE as a performance indicator. Originality/value – Serious games on lean manufacturing have been developed and played for a long time. While some of these games include OEE as an important result parameter, none really demonstrates how it is measured and analyzed.

Measuring overall equipment effectiveness can be rather difficult. Particularly to capture all chronic losses, those losses that occur frequently, often on a daily basis, and often with a rather quick and easy fix without involvement of other support functions. Sporadic losses, on the other hand, such as breakdowns, lack of material or manpower is quite easily logged as it gets noticed. This issue is clearly a bigger one when discussing manual or semi-automatic OEE measurement systems. As a complement to this and as a way of visualizing effects of chronic versus sporadic losses a tool has been developed and tested in a case study in an industrial setting. 

Overall equipment effectiveness (OEE) is a common performance measure used in manufacturing industry to identify and prioritize losses to perform improvement work on in order to increase the effectiveness of equipment. There exist challenges though, both in implementing OEE as well as in running an OEE-program. Some of these challenges include lack of training and awareness, lack of focus, risk of misunderstanding the measure etc. This paper will deal with some of the possible misconceptions within the use of OEE that might arise during implementation or in continuously running an OEE-program. Some of the topics of misconceptions that will be discussed include: no financial issues are taken into consideration; that the factors of availability; performance and quality are not weighted; the connection to productivity is not always clear; the importance of cross-functionality of the measurement and work method; the issue of comparison of OEE results; and last but not least the view on and hunt for world class levels. The paper will discuss these (and some additional ones) theoretically and suggest some counter-Actions so that they may be avoided. 

Purpose The purpose of the study is to test if it, by the use of a survey methodology, is possible to measure managers' awareness on, and specifically if there exist preconceived beliefs on, overall equipment effectiveness (OEE) results. The paper presents the design of the survey methodology as well as a test of the survey in one case company. Design/methodology/approach Actual OEE logs from a case company are collected and a survey on the data is designed and managers at the same case company are asked to answer the survey. The survey results are followed-up by an interview study in order to get deeper insights to both the results of the survey as well as the OEE strategy at the case company. Findings The findings show that the managers at this particular case company, on a general level, does not suffer too much from preconceived beliefs. However, it is clear that the managers have a preconceived belief that lack of material is logged as a loss much more often than what it actually is. Research limitations/implications The test has only been performed with data from one case company within the automotive manufacturing industry and only the managers at that case company has been active in the test. Practical implications The survey methodology can be replicated and used by other companies to find out how aware their employees are on their OEE results and if possible preconceived beliefs exists. Originality/value To the authors' knowledge, this is the first attempt at measuring if preconceived beliefs on OEE results exist.

Manufacturing maintenance has always undergone change and development. With Industry 4.0-related technological development, increasingly more complex machining equipment, and an increased focus on sustainability, maybe more so today than ever. This has led to an increased difficulty in finding competent maintenance employees to recruit. Simultaneously, it increases the need for continuous competence development to retain the existing work force up to date with the challenges of future development. The introduction of these new technologies and demands does not reduce the need of competence in basic maintenance skills though, but rather adds new areas of needed competence, making the maintenance profession increasingly more complex. This paper will, through an interview study of maintenance managers in an international manufacturing company located in nine countries, delve into the issues and present both challenges and enablers in how to work with recruitment and competence development within maintenance.

Companies must enhance total maintenance effectiveness to stay competitive, focusing on both digitalization and basic maintenance procedures. Digitalization offers technologies for data-driven decision-making, but many maintenance decisions still lack a factual basis. Prioritizing efficiency and effectiveness require analyzing equipment history, facilitated by using Computerized Maintenance Management Systems (CMMS). However, CMMS data often contains unstructured free-text, leading to manual analysis, which is resource-intensive and reactive, focusing on short time periods and specific equipment. Two approaches are available to solve the issue: minimizing free-text entries or using advanced methods for processing them. Free-text allows detailed descriptions but may lack completeness, while structured reporting aids automated analysis but may limit fault description richness. As knowledge and experience are vital assets for companies this research uses a hybrid approach by combining Natural Language Processing with domain specific ontology and Large Language Models to extract information from free-text entries, enabling the possibility of real-time analysis e.g., identifying recurring failure and knowledge sharing across global sites.

The “Factory-in-a-Box” concept is currently being developed in a Swedish research project and consists of standardized production modules that are installed in a container and transported by e.g. a truck or by train. The modules may rapidly be combined into production systems that can be reconfigured for a new product and/or scaled to handle new volumes. The key features of this futuristic production system concept are thus flexibility, mobility, and speed. The objective with this paper is to discuss how research within the area of maintenance and condition monitoring will help realizing flexibility, mobility, and speed within the Factory-in-a-Box concept. The paper presents how maintenance will be an important enabler in the Factory-in-a-Box project and will explain and describe how maintenance should be used in achieving high availability.

Today, the drive in many organizations is to focus on reducing production costs while increasing customer satisfaction. One key to succeed with these goals is to develop and improve both quality and maintenance in production as well as quality and maintenance in early phases of the development processes. The purpose of this paper is to discuss how and motivate why research within quality and maintenance development may interact, in order to help companies meet customer demand while at the same time increase productivity. The paper is based on ideas and research perspectives of the newly formed competence group on ‘Quality- and Maintenance Development’ at the School of Innovation, Design and Engineering at the Malardalen University, Sweden. This paper elaborates on the concepts of Quality and Maintenance, its important integration, and provides some examples of ongoing research projects within the competence group.

As more companies have started seeing the maintenance department as a profit generating function more focus has been directed on different maintenance strategies. Total Productive Maintenance (TPM) and Reliability-Centered Maintenance (RCM) are two of the most well known maintenance strategies that in the last 20 years have been used frequently in the manufacturing and aircraft industry. To perform maintenance actions in the corrective or the preventive approach is though still a present issue. The predictive maintenance technology Condition Based Maintenance (CBM) has in the past years been receiving good reviews although it is not to a great extent utilized within Swedish industry. One reason for this might be that there is a lack of organizational research within CBM in terms of implementation strategies and applied CBM, i.e. how to implement and run a successful CBM program. The objective with this paper is to, through a case study, illustrate and highlight important aspects companies have to consider when a decision to implement CBM has arisen. The results of the case are not very controversially and many similarities can be drawn to general literature on change and implementation processes.

This paper presents how a Life cycle cost or Total cost of ownership analysis has been performed on machining equipment in a Swedish company. Life cycle cost models used in case studies are compared to an empirical model, used at the company, where dynamic energy, fluid, and maintenance cost are included. Linear and variable factors in the models are analyzed and discussed regarding data availability and estimation, especially with emphasis on maintenance. The life cycle cost aspect of the equipment give guidelines to consider operation, maintenance, tools, energy, and fluid cost in addition to acquisition cost, when designing/specifying the equipment.

Development and technological advancement within Industry 4.0 is on top of agendas worldwide. The prediction that cost of technology will decrease while computational power will increase may lead to a maintenance community putting too much trust in technological advancement, leaving basic maintenance concepts and management underdeveloped or even unimplemented in the future. This paper will, through a case study, exemplify the importance of combining basic maintenance concepts and management, e.g., early equipment management, predetermined preventive maintenance, and root-cause failure analysis and elimination, with technological advancement, e.g., predictive maintenance, cyber-physical systems, internet of things, and big data, in order to increase total maintenance effectiveness.

Productivity is a key weapon for manufacturing companies to stay competitive in a continuous growing global market. Increased productivity can be achieved through increased availability. This has directed focus on different maintenance types and maintenance strategies. Increased availability through efficient maintenance can be achieved through less corrective maintenance actions and more accurate preventive maintenance intervals. Condition Based Maintenance (CBM) is a technology that strives to identify incipient faults before they become critical which enables more accurate planning of the preventive maintenance. CBM can be achieved by utilizing complex technical systems or by humans manually monitoring the condition by using their experience, normally a mixture of both is used. Although CBM holds a lot of benefits compared to other maintenance types it is not yet commonly utilized in industry. One reason for this might be that the maturity level in complex technical CBM system is too low. This paper will acknowledge this possible reason, although not trying to resolve it, but focusing on system technology with component strategy and an open approach to condition parameters as the objective is fulfilled. This paper will theoretically discuss the technical components of a complete CBM system approach and by a case study illustrate how a CBM system for industrial robot fault detection/diagnosis can be designed using the Artificial Intelligence method Case-Based Reasoning and sound analysis.

The advanced technologies available in the development of Smart Maintenance within Industry 4.0 have the potential to significantly improve the efficiency of industrial maintenance. However, it is important to be careful when deciding which technologies to implement for a given application and when evaluating the quality of the data generated. Otherwise, what should be cost-effective solutions may end up being cost-driving. The use of domain knowledge in selecting, developing, implementing, setting up, and utilizing these technologies is increasingly important for achieving success. In this paper, we will elaborate on this topic by presenting and analyzing insights from industrial cases, drawing on the authors’ extensive experience in the field.

Traditionally, research within maintenance has been viewed from an operations research and maintenance optimization perspective, based on the mathematical theory of reliability. Utilizing an analytical approach with mostly quantitative methods, renewal theory, reliability tests, failure rate estimates, fatigue life in materials, and so on, have been researched and analyzed [1, 2]. However, Dekker [3], for instance, points out that there are, in many areas, complaints about the gap between theory and practice. Thus, in order to help companies realizing a more efficient maintenance execution and benefit from the performed research, other research perspectives might be important as well.

This paper argues for the need of having an applied systems approach when performing research on maintenance design and development. The purpose of having such a research approach is to bridge some of the gap between theory and practice when it comes to development of new innovative philosophies/methodologies/techniques and the implementation of these in industrial contexts. The paper is divided in a Section on introduction and a background to the issue, a Section on the need for research on holistic maintenance, and end with a Section of discussion, presenting some ideas on how to perform research on holistic maintenance and an introduction to the research group on 'Maintenance Development' at Mälardalen University, Sweden.

The objective of this paper is to discuss and elaborate on requirements of maintenance and the resulting maintenance needs in order to maintain said requirements without introducing waste while doing so, taking into account both external and internal wastes. The paper will present, and elaborate on, conceptual models that can be utilized in maintenance operations in order to increase awareness of the importance of well-founded customer/stakeholder requirements in order to articulate appropriate maintenance needs in order to balance effectiveness and efficiency as well as to reduce or eliminate maintenance-related waste.

ENLIGT HEMSIDAN ”www.phrases.org.uk”(2016-02-25) myntade författaren Daniel Defoe frasen ’döden och skatter’ år 1726 och fler har sedan följt i hans fotspår. En av de kanske mest kända formuleringarna kom till i ett samtal mellan Benjamin Franklin och Jean-Baptiste Leroy (1789): ”I denna värld kan ingenting sägas vara säkert, utom döden och skatterna.” (fritt översatt från engelska). Vi har även funnit en person som använt det här uttrycket kopplat till underhåll, nämligen Kevin Marshall som diskuterar underhåll av hyreshus: ”...döden, skatter och underhåll.” (”www.flat-living.co.uk”, 2016-02-25). Underhåll i någon av alla dess former är någonting alla människor på jorden upplever nästan dagligen, medvetet eller omedvetet. Det finns egentligen bara ett sätt att tackla detta – med ett leende på läpparna. Man behöver dock inte vara slösaktig. På samma sätt som väldigt få vill betala mer i skatt än vad lagen kräver så vill sällan någon betala mer för underhåll än vad nöden kräver. Det är vad denna handbok handlar om. Den vänder sig till tillverkande företag som önskar minska sina underhållsrelaterade slöserier, och därför har behov av att se över sin verksamhet. Boken vänder sig i första hand till ledningsgrupper för underhåll, underhållschefer och underhållsutvecklare/ingenjörer. Dock, för att citera en av våra samarbetspartners: ”Det är ett slöseri om bara anställda inom underhållsavdelningen läser boken.” För att nå ett hållbart resultat är vi övertygade om att medvetenheten om slöserier och underhållsrelaterade slöserier behöver höjas bland samtliga anställda i en verksamhet. Detta är anledningen till att vi vill att du använder handboken. Vi uppmanar till att du läser exemplen och diskuterar frågorna med medarbetare inom hela underhållsavdelningen, och gärna tvärfunktionellt med produktion och övriga stödfunktioner. Vårt mål är att ge vägledning för hur tillverkande företag kan arbeta med underhållsrelaterade slöserier. Boken klargör vad sådana slöserier är, samt tips och idéer på hur man kan identifiera, klassificera och kvantifiera dem. Handboken presenterar även en arbetsprocess för att minska eller ta bort underhållsrelaterade slöserier så kostnadseffektivt som möjligt. Den innehåller också korta teoriavsnitt med exempel från praktiken och frågor som ledningsgrupper och anställda inom verksamheten kan diskutera. Genom att följa arbetsprocessen kan du och ditt företag få ökad medvetenhet och förståelse för underhållsrelaterade slöserier inom er egen verksamhet. Handboken fokuserar främst på de tidiga stegen i processen eftersom de är mest avgörande för ett lyckat resultat. Underhållsrelaterade slöserier är delvis unika för varje företag. Tyvärr finns inga genvägar eller standarder för att minska eller ta bort dem. Att endast läsa handboken kommer inte att ge något resultat. Den här boken bygger på att du och ditt företag aktivt finner er egen väg för att minska eller ta bort de underhållsrelaterade slöserier ni upptäcker i er verksamhet.

The result of today’s global and increasingly tough competition is narrow market windows and a demand for quick volume increases in production. This in turn means increased demands for a rapid and effective development of production equipment that ensures high performance right at the start of production. Robust production equipment with a high level of production efficiency and reduced costs for operation and maintenance therefore make up one of the most important factors for strong competitiveness and high profitability for Swedish industrial enterprises. Strong collaboration between users and suppliers is the key to success in this type of investment project. This handbook therefore presents a model that can be used by manufacturing companies who want to develop robust production equipment. The model and the other recommendations of the handbook focus on projects that are to be carried out in strong collaboration and are targeted at both users and suppliers. The model has been deve-loped through “EQUIP – User-supplier integration in production equipment design”, which has received funding from the Knowledge Foundation 2013–2016. The model consists of seven development phases based on the production equipment life cycle: Phase 1 – Preliminary study Phase 2 – Concept study Phase 3 – Procurement Phase 4 – Detailed design Phase 5 – Construction Phase 6 – Installation and commissioning Phase 7 – Production In each phase, critical activity steps and recommendations are presented for how to distribute responsibility within and between the parties involved. The model adopts a life cycle perspective for development projects in order to facilitate collaboration and to more clearly visualise the link between activities and their impact on the project success. Within the scope of an investment project, there is a great potential for developing sustainable production solutions. For this reason, this handbook also presents seven guidelines that may provide you with support in developing production equipment that remains secure, lean and sustainable throughout the equipment life cycle. The main purpose of the handbook is to facilitate collaboration through the whole investment project in a way that benefits both parties and which contributes to lasting relationships. The results of the research project show that there is a great interest in improved collaboration from both users and suppliers. For this reason, support, tools and preparedness from both parties are required to venture into investing time and resources in collaboration from the beginning, in the early phases of a new development project. This is then the potential to lay the foundation for long-term collaboration and for designing the best possible production equipment in the shortest time possible.

Av dagens globala och allt hårdare konkurrens följer korta marknadsfönster och krav på snabb volym- uppgång i produktion. Det innebär i sin tur ökade krav på snabb och effektiv utveckling av produktions- utrustning som säkerställer hög prestanda direkt vid produktionsstart. Robust produktionsutrustning med hög produktionseffektivitet och minskade kostnader för drift och underhåll är därför en av de viktigaste faktorerna för stark konkurrenskraft och hög lönsamhet för svenska industriföretag. God samverkan mellan beställare och leverantör är nyckeln till framgång i denna typ av investerings- projekt. Denna handbok presenterar därför en modell som kan användas av tillverkande företag som vill utveckla robust produktionsutrustning. Modellen och övriga rekommendationer i handboken fokuserar på projekt som ska genomföras i stark samverkan och riktar sig till både beställaren och leverantören. Den har utvecklats i forskningsprojektet ”EQUIP – kund- och leverantörsintegration i utformning av produktionsutrustning” som finansierats av KK-stiftelsen under 2013-2016. Modellen består av sju utvecklingsfaser som är baser- ade på produktionsutrustnings livscykel: Fas 1 – Förstudie Fas 2 – Konceptstudie Fas 3 – Upphandling Fas 4 – Detaljerad utformning Fas 5 – Uppbyggnad Fas 6 – Installation och driftsättning Fas 7 – Produktion I varje fas presenteras kritiska aktivitetssteg och rekommendationer för hur ansvaret för dessa bör fördelas inom och emellan deltagande parter. Modellen använder ett livscykelperspektiv för utvecklingsprojekt för att underlätta samverkan samt tydligare visualisera sambandet mellan aktiviteter och deras påverkan på projektets framgång. Inom ramen för ett investeringsprojekt finns stor potential att utveckla hållbara produktionslösningar. Därför presenterar denna handbok även sju guider som kan stödja er i att ta fram produktionsutrustning som är säker, lean och hållbar under hela utrustningens livscykel. Huvudsyftet med handboken är att underlätta samverkan under hela investeringsprojektet på ett sätt som gagnar båda parter och bidrar till varaktiga relationer. Forskningsprojektets resultat visar att det finns ett stort intresse för främjad samverkan från både beställ- are och leverantör. Därför behövs stöd, verktyg och beredskap från båda parter för att våga investera tid och resurser på samverkan redan från början, i de tidiga faserna av ett nytt utvecklingsprojekt. Det är då potentialen att lägga grunden till långsiktig samverkan och utforma bästa möjliga produktionsutrustning på kortast möjliga tid är som störst.

Mälardalen Univerity is characterised by its close collaboration with companies and with the public sector in the region. A main strategic directions of the university is to develop co-production with partner companies, expressed in the university vision “A Strong MDH – the Coproducing University”. The concept ’co-production’ is in this paper used interchangeably with concept ’co-creation’, emphasising our view of equal participation and interaction with the goal of knowledge, that by the company can be made useful outside the university (see Terblanche, 2014). Based on Mälardalen University’s vision, co-production is a main goal for the Innovation and Product Realization (IPR) environment. IPR is located at the School of Innovation, Design and Engineering and has a common graduate education with three mutually supportive cooperating research groups: Product realization, Innovation management, and Information design. Here ideas from different fields and cultures meet, creating new ideas, possibilities, and knowledge as a result. The approach to develop new insights and knowledge in order to address societal challenges, through working closer between academics and research users, has a potential to improve how research is conducted. Still, there are many questions and challenges in this approach, with need of development: How is research and research education framed and undertaken? What constitutes co-production? What distinguishes reseach in co-production from other forms of research? What are the benefits and barriers of co-production? As we shall see, the follow-up research aim to contribute to how our third level education in a co-production environment can be undertaken.

The reuse of experiences gained in maintenance activities is important issue in maintenance management. Efficient experience reuse would improve next interventions, reduce the mistakes and potentially contribute to time and cost savings. However, few studies focus on how maintenance workforce reuses past experiences in the problem- solving phases of the maintenance work. The purpose of this study is therefore to examine the experience reuse process in production maintenance in order to identify reuse practices and its challenges. Based on a case study, this paper presents the observed work practices and its challenges for collecting and reusing experiences in production maintenance. Further, potential improvement suggestions are proposed to overcome these challenges.

Ontology development plays a vital role as it provides a structured way to represent and organize knowledge. It has the potential to connect and integrate data from different sources, enabling a new class of AI-based services and systems such as decision support systems and recommender systems. However, in large manufacturing industries, the development of such ontology can be challenging. This paper presents a use case of an application ontology development based on machine breakdown work orders coming from a Computerized Maintenance Management System (CMMS). Here, the ontology is developed using a Knowledge Meta Process: Methodology for Ontology-based Knowledge Management. This ontology development methodology involves steps such as feasibility study, requirement specification, identifying relevant concepts and relationships, selecting appropriate ontology languages and tools, and evaluating the resulting ontology. Additionally, this ontology is developed using an iterative process and in close collaboration with domain experts, which can help to ensure that the resulting ontology is accurate, complete, and useful for the intended application. The developed ontology can be shared and reused across different AI systems within the organization, facilitating interoperability and collaboration between them. Overall, having a well-defined ontology is critical for enabling AI systems to effectively process and understand information.

Experienced staffs acquire their experience during many years of practice, and sometimes also through expensive mistakes. This knowledge is often lost when technicians retire, or if companies need to downsize during periods of reduced sale. When scaling up production, new staff requires training and may repeat similar mistakes. Another issue that may be costly is when monitoring systems repeatedly give false alarms, causing expensive loss of production capacity and resulting in technicians losing trust in the systems and in worst case, switch them off. If monitoring systems could learn from previous experience for both correct and false alarms, the reliability and trust in the monitoring systems would increase. Moreover, connecting alarms to either equipment taking automatic actions or recommend actions based on the current situations and previous experience would be valuable.

An engineer repeating the same task a second time is often able to perform the task in 1/3 of the time it took at the first time. Most corrective and preventive actions for a particular machine type have been carried out before. This past experience holds a large potential for time savings, predictability and reduced risk if an efficient experience transfer can be accomplished. But building large complex support system is not always the ideal way. We propose instead localized intelligent agents, able to either autonomously perform the necessary actions or aid a human in the decision making process by providing the necessary information needed to make an informed and validated decision.