1. |
- Bärring, Maja, 1988, et al.
(author)
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5G Enabled Manufacturing Evaluation for Data-Driven Decision-Making
- 2018
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In: Procedia CIRP. - : Elsevier BV. - 2212-8271. ; 27, s. 266-271
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Conference paper (peer-reviewed)abstract
- Manufacturing industries are experiencing a technical paradigm shift that will change how they run their operations. Equipment and personnel generate an ever-increasing amount of data, and connectivity enables to utilize data to a larger extent. Connecting a machine is not a technical obstacle anymore, but with all available data, the challenge is to understand the requirements of data to support efficient decision-making. This paper will address the requirements of data by domain experts, in the context of more real-time data available. A focus group interview was performed, assessing the key factors of big data; volume, velocity, and variety of data.
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2. |
- Karlsson, Nadine, 1988, et al.
(author)
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QUANTIFYING THE EFFECTS OF PRODUCTION MAINTENANCE DECISIONS USING DISCRETE EVENT SIMULATION
- 2014
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In: Swedish Production Symposium, 2014, Gothenburg.
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Conference paper (peer-reviewed)abstract
- Use of simulation to analyze and plan maintenance activities is still limited compared to planning production activities. The paper discusses a simulation based approach to quantify the effects of maintenance decision making by identifying the related performance indicators. The aim of the paper is to quantify the production maintenance related decisions, in terms of Key Performance Indicators (KPIs) determined trough interwievs and simulation. The approach is exemplified in a manufacturing case-study. The results show that use of simulation tool has the potential to be a strategic decision support tool for production maintenance in the production system.
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3. |
- Lundgren, Camilla, 1989, et al.
(author)
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A Strategy Development Process for Smart Maintenance Implementation
- 2021
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In: Journal of Manufacturing Technology Management. - 1741-038X. ; 32:9, s. 142-166
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Journal article (peer-reviewed)abstract
- Technological advancements are reshaping the manufacturing industry toward digitalized manufacturing. Despite the importance of top-class maintenance in such systems, many industrial companies lack a clear strategy for maintenance in digitalized manufacturing. The purpose of this paper is to facilitate the implementation of maintenance in digitalized manufacturing by proposing a strategy development process for the Smart Maintenance concept. A process of strategy development for smart maintenance is proposed, including six steps: benchmarking, setting clear goals, setting strategic priority, planning key activities, elevating implementation and follow-up. The proposed process provides industry practitioners with a step-by-step guide for the development of a clear smart maintenance strategy, based on the current state of their maintenance organization. This creates employee engagement and is a new way of developing maintenance strategies.
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4. |
- Lundgren, Camilla, 1989, et al.
(author)
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Challenges Building a Data Value Chain to Enable Data-Driven Decisions: A Predictive Maintenance Case in 5G-Enabled Manufacturing
- 2018
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In: Procedia Manufacturing. - : Elsevier BV. - 2351-9789. ; 17, s. 411-418
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Conference paper (peer-reviewed)abstract
- Improvements in data storage and processing technologies have led many managers to change how they make decisions, relying less on intuition and more on data. This trend is especially notable for the manufacturing industry where Big Data applications, i.e. data analytics, are mentioned as an important enabler of value creation with the event of the fourth industrial revolution. Designing and building the entire data value chain that enables Big Data applications in manufacturing requires new knowledge about digital technologies combined with already established knowledge about the specific manufacturing processes. This paper focuses on the convergence of these different knowledge spaces applied to a specific case of implementing a Big Data application for predictive maintenance. Every step of building the data value chain from data acquisition to system feedback is presented and discussed in terms of the major challenges that were observed during the project. Results show that, just as the literature suggests, the knowledge gaps between different domains is a key component to manage for succeeding when building Big Data applications in the context of future manufacturing and maintenance.
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5. |
- Lundgren, Camilla, 1989, et al.
(author)
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Determining the impact of 5G-technology on manufacturing performance using a modified TOPSIS method
- 2022
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In: International Journal of Computer Integrated Manufacturing. - 0951-192X .- 1362-3052. ; 35:1, s. 69-90
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Journal article (peer-reviewed)abstract
- A digital transformation is currently taking place in society, where people and things are connected to each other and the Internet. The number of connected devices is projected to be 28 Billion in 2025, and our expectations on digitalization set new requirements of mobile communication technology. To handle the increased amount of connected devices and data generated, the next generation of mobile communication technology is under deployment: 5G-technology. The manufacturing industry follows the digital transformation, aiming for digitalized manufacturing with competitive and sustainable production systems. 5G-technology meets the connectivity requirements in digitalized manufacturing, with low latency, high data rates, and high reliability. Despite these technological benefits, the question remains: Why should the manufacturing industry invest in 5G-technology? This study aims to determine the impact of 5G-technology on manufacturing performance; based on a mixed-methods approach including a modified TOPSIS method to ensure robustness of the results. The results show that 5 G-technology will mainly impact productivity, maintenance performance, and flexibility. By linking 5G-technology to the performance of the manufacturing system, instead of focusing on network performance, the benefits of using 5G-technology in manufacturing become clear, and can thus facilitate investment and deployment of 5G-technology in the manufacturing industry.
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6. |
- Lundgren, Camilla, 1989
(author)
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Facilitating the Implementation of Smart Maintenance
- 2021
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Doctoral thesis (other academic/artistic)abstract
- Innovations and rapid advancements in digital technologies in the manufacturing industry are setting high expectations of highly automated, intelligent and interconnected production systems. To bring these expectations to realisation and secure productive and sustainable production systems, maintenance organisations must develop accordingly. Thus, there is a need for organisational innovation in maintenance. The way in which maintenance is organised in digitalised manufacturing is called “Smart Maintenance”, and industrial companies need evidence‐based guidance in pursuing such an implementation. Thus, the purpose of this thesis is to facilitate Smart Maintenance implementation. To this end, the thesis aims to support organisational innovation in maintenance, with organisations and all targeted employees becoming increasingly skilful, consistent and committed to working with Smart Maintenance. This aim was achieved through a mixed‐methods approach comprising six studies. Firstly, digitalisation in general and Smart Maintenance in particular, will require investment. This thesis reviews 24 maintenance models which can be used as support in calculating and describing the effects of maintenance. It also demonstrates an example of how to evaluate new technology (the impact of 5G technology on manufacturing performance). The thesis also identifies 11 factors influencing the investment process. Secondly, to benefit from the technology, an organisation must develop accordingly. This means that development initiatives need to be managed. This thesis presents an overall consideration model for leading maintenance in digitalised manufacturing. In short, the role of a maintenance manager is changing from that of a technical manager into a leader of people and organisations in change. Further, the effects of Smart Maintenance can be followed up using maintenance performance indicators (PIs). This thesis analyses 170 PIs and structures them into 13 categories. Thirdly, a strategic approach to Smart Maintenance helps in structuring such an implementation. This thesis proposes a strategy development process for Smart Maintenance implementation. The process is cyclical and continuously assesses the maintenance organisation to find new improvement areas. It thus continuously develops maintenance organisations and their way of working with Smart Maintenance. All studies are related to the diffusion of innovations (DOI) theory, to structure the findings into a framework that supports organisational innovation in maintenance. This is a novel perspective in both research and practice. The framework provided in this thesis can be used as guidance by industry practitioners as they implement Smart Maintenance. Thus, industrial companies can continue their development towards digitalisation and move towards increasingly competitive and sustainable production systems.
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7. |
- Lundgren, Camilla, 1989, et al.
(author)
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Factors influencing maintenance-related investments in industry: a multiple-case study
- 2021
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In: Journal of Quality in Maintenance Engineering. - 1355-2511. ; 27:1, s. 203-224
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Journal article (peer-reviewed)abstract
- Purpose: The purpose of this study is to ensure productive, robust and sustainable production systems by enabling future investments in maintenance. This study aims to provide a deeper understanding of the investment process and thereby facilitate future maintenance-related investments. The objectives are to describe the investment process, map the decision support and roles involved and identify factors influencing the process. Design/methodology/approach: The study was designed as a multiple-case study, with three industrial cases of maintenance-related investments. A structured coding procedure was used to analyse the empirical data from the cases. Findings: This paper provides a deeper understanding of the process of maintenance-related investments. Eleven factors influencing the investment process could be identified, three of which were seen in all three cases. These three factors are: fact-based decision-support, internal integration and foresight. Practical implications: Investments in modern maintenance are needed to ensure productive, robust and sustainable production in the future. However, it is a challenge in manufacturing industry to justify maintenance-related investments. This challenge may be solved by developing a decision-support system, or a structured work procedure, that considers the findings of this study. Originality/value: From this study, an extended view of the relation between quantifying effects of maintenance and maintenance-related investment is proposed, including surrounding factors influencing the investment process. The factors were identified using a structured and transparent coding procedure which is rarely used in maintenance research.
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8. |
- Lundgren, Camilla, 1989, et al.
(author)
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Hindering Factors in Smart Maintenance Implementation
- 2022
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In: Advances in Transdisciplinary Engineering. ; 21, s. 629-637
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Conference paper (peer-reviewed)abstract
- In today’s industrial environment, innovations and advancements in technology are extremely fast. This development has led to a Fourth Industrial Revolution where industrial companies strive to achieve highly digitalized and resilient production systems. To realize such production systems, the role of maintenance is critical. Industrial companies are anticipated to transform their maintenance organizations towards Smart Maintenance, but they need evidence-based guidance in pursuing such an implementation. Thus, the purpose of this paper is to support industry practitioners in their Smart Maintenance implementation. By means of an empirical case study within energy production, this paper identifies and describes hindering factors that impede the implementation of Smart Maintenance, as well as provides recommendations for overcoming the hindering factors. The recommendations can be used by industry practitioners to increase the likelihood of success in their Smart Maintenance implementation, thereby helping industrial companies in their development of sustainable and resilient production systems.
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9. |
- Lundgren, Camilla, 1989, et al.
(author)
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How industrial maintenance managers perceive socio-technical changes in leadership in the Industry 4.0 context
- 2023
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In: International Journal of Production Research. - : Informa UK Limited. - 0020-7543 .- 1366-588X. ; 61:15, s. 5282-5301
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Journal article (peer-reviewed)abstract
- Innovations and advancements in technology create new opportunities to run and maintain manufacturing plants, which we refer to as digitalised manufacturing. This development is recognised as a socio-technical system (STS) change, where a change in the production system’s goals, technology, processes, people, or environment may lead to ripple effects between those sub-systems. Despite this, technology development and technology use cases account for most of the research within digitalised manufacturing, while little attention has been devoted to leadership practices considering digitalised manufacturing from a socio-technical perspective. This paper focuses on the maintenance organisation, whose mission in a company is to keep production systems functional. We aim to describe leadership in industrial maintenance from an STS perspective. This is a unique interview study where twenty maintenance managers from Swedish manufacturing industry offer their perspective on the changing leadership within maintenance, providing a unique insight into the challenges facing leaders of maintenance in digitalised manufacturing. We frame the empirical findings using an STS framework and propose an overall consideration model for leadership that supports the development of a functional maintenance organisation in the face of pervasive digitalisation.
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10. |
- Lundgren, Camilla, 1989, et al.
(author)
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Performance indicators for measuring the effects of Smart Maintenance
- 2020
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In: International Journal of Productivity and Performance Management. - 1741-0401. ; 70:6, s. 1291-1316
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Journal article (peer-reviewed)abstract
- Purpose – The purpose of this study is to ensure productive, robust and sustainable production systems and realise digitalised manufacturing trough implementation of Smart Maintenance – “an organizational design for managing maintenance of manufacturing plants in environments with pervasive digital technologies”. This paper aims to support industry practitioners in selecting performance indicators (PIs) to measure the effects of Smart Maintenance, and thus facilitate its implementation. Design/methodology/approach – Intercoder reliability and negotiated agreement were used to analyse 170 maintenance PIs. The PIs were structurally categorised according to the anticipated effects of Smart Maintenance. Findings – Companies need to revise their set of PIs when changing manufacturing and/or maintenance strategy (e.g. reshape the maintenance organisation towards Smart Maintenance). This paper suggests 13 categories of PIs to facilitate the selection of PIs for Smart Maintenance. The categories are based on 170 PIs, which were analysed according to the anticipated effects of Smart Maintenance. Practical implications – The 13 suggested categories bring clarity to the measuring potential of the PIs and their relation to the Smart Maintenance concept. Thereby, this paper serves as a guide for industry practitioners to select PIs for measuring the effects of Smart Maintenance. Originality/value – This is the first study evaluating how maintenance PIs measure the anticipated effects of maintenance in digitalised manufacturing. The methods intercoder reliability and negotiated agreement were used to ensure the trustworthiness of the categorisation of PIs. Such methods are rare in maintenance research.
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