Per Schjølberg - Academia.edu (original) (raw)

Papers by Per Schjølberg

Advanced Manufacturing and Automation VIII, 2018

To stay competitive in the future, industrialists must be prepared to adopt the imminent changes ... more To stay competitive in the future, industrialists must be prepared to adopt the imminent changes and new technologies associated with Industrie 4.0. These changes apply equally to the field of maintenance, which is also developing quickly. Sensors, along with analyses and competence, are one of the most critical factors for Industrie 4.0 as they are the connectors between the digital and physical world. Utilization of these sensors within maintenance is a relatively unexplored field. Thus, the aim of this paper is to present a novel concept for ways sensor management can be linked to maintenance and thereby improve operational availability. The paper also presents an overview of sensor management and trends within maintenance.

Engineering Assets and Public Infrastructures in the Age of Digitalization

The balance between maintenance and production activities plays a pivotal role for any asset in a... more The balance between maintenance and production activities plays a pivotal role for any asset in an organisation. Maintenance activities can require that the asset must be unavailable for production during maintenance and hence reduce the production volume. However, if the asset is not maintained the technical condition will degrade and can result in unexpected breakdowns and reduced plant capacity. An important question will then be: How can an organisation ensure the right balance of maintenance during the lifetime of the asset? To approach this question, a fundamental understanding in asset management and strategic approach in an organisation is indeed necessary. The standard EN16646 gives further detail of the interrelationship between maintenance and other processes at asset and asset system level. Although a list is provided, it remains to investigate how the relationship between operation and maintenance processes can contribute to an asset management strategy. The objective of this article is therefore to propose an approach in asset management strategy that will ensure a right balance between plant capacity and maintenance activities during the life cycle of an asset.

Hydropower companies have good technical competence and good knowledge of the plants, even though... more Hydropower companies have good technical competence and good knowledge of the plants, even though they still can utilize their knowledge more systematically. The improvement potential is high when it comes to apply new methods, tools, information about technical condition, operating history and indicators for continuous improvement of the maintenance function. Deterioration of hydropower components will increase due to new operation strategies and age, and hence increase the risk related to hydropower. Risk-based maintenance management must be implemented in order to meet these challenges. The Optimal Maintenance Toolbox described in the paper is developed for that purpose. The Toolbox with its Failure model constitutes a knowledge-based framework for continuous improvement of the maintenance management processes. Monitoring of risk and action needs indicators shall help the maintenance staff to identify unacceptable risk due to deterioration and to take appropriate actions. Mainten...

Advanced Manufacturing and Automation VIII, 2018

To have a maintenance function in the company that ensures a competitive advantage in the world m... more To have a maintenance function in the company that ensures a competitive advantage in the world market requires the world class maintenance (WCM). Though several different periods in history, maintenance has shifted from reactive maintenance fixing it when it breaks towards more systematic analysis techniques in terms of root cause analysis. With the onset of digitalisation and the breakthrough technologies in from Industry 4.0 more advanced analytics are expected in WCM. In particular the indicator profit loss indicator (PLI) has shown promising results in measuring e.g. time losses in production in a monetary term. Further, this indicator has also been proposed to be included in predictive maintenance. However, it is not pointed out clearly which role PLI will have in WCM. The aim of this article is therefore to investigate the trends of WCM as well as how PLI can be included in this journey.

The fourth industrial revolution is expected to bring substantial changes to how maintenance will... more The fourth industrial revolution is expected to bring substantial changes to how maintenance will be conducted in the upcoming years. In this paper three main areas of technology innovation related to how Industry 4.0 can change maintenance and asset management have been identified: smart maintenance, smart working and smart products. However, implementing new technology is only part of the picture, and several resent papers have pointed to the importance of organizational factors. But it is also important to include economic factors when developing strategies to implement Industry 4.0 in maintenance and asset management. In this paper a model that does just that is proposed. This is done by utilizing a concept called Economic Value Added (EVA) and a more recent offspring in the domain of maintenance and asset management labeled Value Driven Maintenance (VDM) sensitivity analysis. An example of how the recent technology development in combination with economic preconditions can be u...

Advanced Manufacturing and Automation VIII, 2018

To stay competitive in the future, industrialists must be prepared to adopt the imminent changes ... more To stay competitive in the future, industrialists must be prepared to adopt the imminent changes and new technologies associated with Industrie 4.0. These changes apply equally to the field of maintenance, which is also developing quickly. Sensors, along with analyses and competence, are one of the most critical factors for Industrie 4.0 as they are the connectors between the digital and physical world. Utilization of these sensors within maintenance is a relatively unexplored field. Thus, the aim of this paper is to present a novel concept for ways sensor management can be linked to maintenance and thereby improve operational availability. The paper also presents an overview of sensor management and trends within maintenance.

Maintenance has traditionally been seen as a costly and unwanted evil. Nowadays, the view of main... more Maintenance has traditionally been seen as a costly and unwanted evil. Nowadays, the view of maintenance has changed, as new maintenance technologies and Smart Maintenance have proven to give competitive advantages for industrialists. Additionally, increased global competition and need for improving manufacturing performance has resulted in more focus on company’s maintenance function. Another field of interest, is how modern value chains can support the maintenance function in a company. Research on the field of value chain and maintenance has mainly been carried out independently, and research on how these two fields can be combined and utilized to strengthen each other seem to have just launched the start line. This is especially true when it comes to the area of improving maintenance programs, which traditionally have been static, inflexible, and inefficient. Thus, the aim of this paper is therefore to investigate on how maintenance programs can benefit from including a value ch...

Proceedings of the 6th International Workshop of Advanced Manufacturing and Automation, 2016

This paper is focused on how principles from Industry 4.0 in manufacturing can be used in operati... more This paper is focused on how principles from Industry 4.0 in manufacturing can be used in operation and maintenance of subsea production systems. The primary purpose and goal of the paper is to investigate the application of Smart Maintenance to achieve high level of safety, availability and profit in operation and maintenance of subsea production systems. The paper describes state-of-the-art in Smart Maintenance. This includes the framework for intelligent predictive maintenance, use of artificial intelligence for condition monitoring purposes and the progression of technologies for Smart Maintenance. The procedures for maintenance of Ormen Lange subsea choke modules are outlined. The paper investigates the performance of procedures for maintenance of Ormen Lange subsea choke modules, as compared to state-of-the-art in Smart Maintenance.The results are presented, as well a short conclusion. Suggestion for further work includes performing a quantitative Life Cycle Profit (LCP) analysis to investigate return on investment for further implementation of Smart Maintenance for Ormen Lange subsea choke modules.

Safety and Reliability – Safe Societies in a Changing World, Jun 15, 2018

With the onset of Industry 4.0 several technological possibilities are offered in industry such a... more With the onset of Industry 4.0 several technological possibilities are offered in industry such as big data analytics, digital twin and augmented reality. The result is a more digitalised industry where faster and better decisions are possible. In long term this should provide a more reliable production with increased plant capacity and reduced downtime. To succeed with these possibilities a Cyber Physical Systems (CPS) must be established for the company. Currently, an own framework for CPS is under development and is expected to be tailored for Norwegian manufacturing. When building on the principle in Industry 4.0, big data capability with machine learning will be a fundamental model. Nevertheless, Industry 4.0 should also include other models for big data capability such as reliability modelling. The aim in this article is to present the current status of CPS framework and how it could be implemented in manufacturing industries. In particular, the article discusses and demonstrates the balance between machine learning and reliability engineering in big data analytics.

Proceedings of the 6th International Workshop of Advanced Manufacturing and Automation, 2016

With the current situation of high demand of sustainable manufacturing, different stakeholders ha... more With the current situation of high demand of sustainable manufacturing, different stakeholders have clear expectations for more environmental manufacturing and at the same time minimizing the operational costs. The role of maintenance plays a key role in the path towards sustainable manufacturing. For achieving green manufacturing, more datadriven predictive maintenance strategies is needed and is expected to reduce energy consumption, maintenance resources in terms of spare parts, and reduction of consumables in terms of example lubrication. The overall bottom-line for the predictive maintenance strategy is increased availability, reduction of maintenance hours in terms of reactive maintenance activities, and increased profit for the manufacturing business. For a predictive maintenance strategy, it is crucial to develop Key Performance Indicators (KPIs) for the maintenance management. Today, common KPIs such as availability and different indicators for maintenance cost has been developed. When aiming for more green manufacturing, a more integrated application of maintenance KPIs are needed. Today, the KPI Profit Loss Indicator (PLI) has been developed and demonstrated in the saw mill industry and is regarded to support a more integrated approach in terms of Integrated Planning (IPL). The aim of this article is develop a structured approach for data-driven predictive maintenance aligned with the concept of PLI. Through a case study, the approach is partly demonstrated for the manufacturing industry. The results in this demonstration shows that the data-driven maintenance strategy will have a positive impact of the PLI value and provide a sustainable manufacturing in long-term.

Proceedings of the 6th International Workshop of Advanced Manufacturing and Automation, 2016

This abstract is an introduction to the next generation of High Performance Industrial Manufactur... more This abstract is an introduction to the next generation of High Performance Industrial Manufacturing, through the Industry standard 4.0. The fourth Industrial standard is based on advanced Automation and Robotics, sensor based computer technology, interconnected by wireless communication, and supported by BIG Data solutions. Effective management and human cooperation i.e. teamwork and SUM© processes will be increasingly important in the future. This paper also focuses on the new industrial standard in relation to OEE (Overall Equipment Effectiveness), Predictive Maintenance and total performance related to all equipment in the industrial factory processes. Not a few highly automated machines, but the system as whole. OEE is a well-known standardized tool for performance measurement throughout the industry. In order to utilize data systems as ERP (Enterprise Resource Planning) and PLM (engineering systems), they must be integrated with business systems. Management normally acts on the bases of facts and financial performance. In most companies increased profit is the overall goal. Future management systems aim for a fully integrated and automated data flow based on advanced sensor technology. Increased use of digital systems enables quicker and better decisions. Refers to previous paper "High Performance Innovative teams (IWAMA 2010).

Advanced Manufacturing and Automation VII, 2018

With the immense pressure to sustain competitive in European manufacturing, the strategy of digit... more With the immense pressure to sustain competitive in European manufacturing, the strategy of digitalizing in this industry sector is indeed necessary. With the onset of new ICT technology and big data capabilities, the physical asset and data computation is integrated in manufacturing through Cyber Physical Systems (CPS). This strategy also denoted as Industry 4.0 will also improve the maintenance function significantly in manufacturing. In particular, maintenance planning will be more synchronized in production scheduling. The aim of this article is to develop an integrated planning (IPL) approach that synchronizes production and maintenance planning with predictive maintenance capability. The result in this article is based on a case study and simulation of manufacturing equipment. In particular, application of key performance indicators (KPIs) is shown to be essential when running the synchronizing mechanism in IPL. The scientific application of the case study is alignment of the IPL theory and new approach in maintenance planning. Furthermore, the application to practice is improved maintenance planning in IPL that increases a reliable plant capacity. It is concluded that the IPL approach should be considered to be a generic platform for manufacturing industry that should be demonstrated further in other manufacturing branches in Europe.

WIT transactions on engineering sciences, 2016

With the challenges of “silo thinking” in production and manufacturing, several disciplines and d... more With the challenges of “silo thinking” in production and manufacturing, several disciplines and departments perform activities that affect each other, which can lead to suboptimal results in production with respect to extra costs and lack of production assurance. For maintenance management, silo thinking may result in unplanned maintenance activities, which may impede production plans. As a remedy to avoid this challenge, a key performance indicator (KPI) for maintenance management has been developed and is denoted as profit loss indicator (PLI). The purpose of this research was to investigate how this indicator can be further developed with more perspectives of concepts of Toyota Production System and Six Sigma. In particular, this PLI is evaluated for a relevant example in the industry with a case study. Results from both literature and case study are used to build further on the PLI concept.

Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems

Advances in Manufacturing

With the emergence of Industry 4.0, maintenance is considered to be a specific area of action tha... more With the emergence of Industry 4.0, maintenance is considered to be a specific area of action that is needed to successfully sustain a competitive advantage. For instance, predictive maintenance will be central for asset utilization, service, and after-sales in realizing Industry 4.0. Moreover, artificial intelligence (AI) is also central for Industry 4.0, and offers data-driven methods. The aim of this article is to develop a new maintenance model called deep digital maintenance (DDM). With the support of theoretical foundations in cyber-physical systems (CPS) and maintenance, a concept for DDM is proposed. In this paper, the planning module of DDM is investigated in more detail with realistic industrial data from earlier case studies. It is expected that this planning module will enable integrated planning (IPL) where maintenance and production planning can be more integrated. The result of the testing shows that both the remaining useful life (RUL) and the expected profit loss indicator (PLI) of ignoring the failure can be calculated for the planning module. The article concludes that further research is needed in testing the accuracy of RUL, classifying PLI for different failure modes, and testing of other DDM modules with industrial case studies.

Journal of Quality in Maintenance Engineering

Purpose -The aim of this article is to develop a novel model for maintenance backlog of physical ... more Purpose -The aim of this article is to develop a novel model for maintenance backlog of physical assets and structure it in a framework for Integrated Planning.

Lecture Notes in Mechanical Engineering, 2016

Advanced Materials Research, Nov 26, 2014

Advanced Manufacturing and Automation VIII, 2018

To stay competitive in the future, industrialists must be prepared to adopt the imminent changes ... more To stay competitive in the future, industrialists must be prepared to adopt the imminent changes and new technologies associated with Industrie 4.0. These changes apply equally to the field of maintenance, which is also developing quickly. Sensors, along with analyses and competence, are one of the most critical factors for Industrie 4.0 as they are the connectors between the digital and physical world. Utilization of these sensors within maintenance is a relatively unexplored field. Thus, the aim of this paper is to present a novel concept for ways sensor management can be linked to maintenance and thereby improve operational availability. The paper also presents an overview of sensor management and trends within maintenance.

Engineering Assets and Public Infrastructures in the Age of Digitalization

The balance between maintenance and production activities plays a pivotal role for any asset in a... more The balance between maintenance and production activities plays a pivotal role for any asset in an organisation. Maintenance activities can require that the asset must be unavailable for production during maintenance and hence reduce the production volume. However, if the asset is not maintained the technical condition will degrade and can result in unexpected breakdowns and reduced plant capacity. An important question will then be: How can an organisation ensure the right balance of maintenance during the lifetime of the asset? To approach this question, a fundamental understanding in asset management and strategic approach in an organisation is indeed necessary. The standard EN16646 gives further detail of the interrelationship between maintenance and other processes at asset and asset system level. Although a list is provided, it remains to investigate how the relationship between operation and maintenance processes can contribute to an asset management strategy. The objective of this article is therefore to propose an approach in asset management strategy that will ensure a right balance between plant capacity and maintenance activities during the life cycle of an asset.

Hydropower companies have good technical competence and good knowledge of the plants, even though... more Hydropower companies have good technical competence and good knowledge of the plants, even though they still can utilize their knowledge more systematically. The improvement potential is high when it comes to apply new methods, tools, information about technical condition, operating history and indicators for continuous improvement of the maintenance function. Deterioration of hydropower components will increase due to new operation strategies and age, and hence increase the risk related to hydropower. Risk-based maintenance management must be implemented in order to meet these challenges. The Optimal Maintenance Toolbox described in the paper is developed for that purpose. The Toolbox with its Failure model constitutes a knowledge-based framework for continuous improvement of the maintenance management processes. Monitoring of risk and action needs indicators shall help the maintenance staff to identify unacceptable risk due to deterioration and to take appropriate actions. Mainten...

Advanced Manufacturing and Automation VIII, 2018

To have a maintenance function in the company that ensures a competitive advantage in the world m... more To have a maintenance function in the company that ensures a competitive advantage in the world market requires the world class maintenance (WCM). Though several different periods in history, maintenance has shifted from reactive maintenance fixing it when it breaks towards more systematic analysis techniques in terms of root cause analysis. With the onset of digitalisation and the breakthrough technologies in from Industry 4.0 more advanced analytics are expected in WCM. In particular the indicator profit loss indicator (PLI) has shown promising results in measuring e.g. time losses in production in a monetary term. Further, this indicator has also been proposed to be included in predictive maintenance. However, it is not pointed out clearly which role PLI will have in WCM. The aim of this article is therefore to investigate the trends of WCM as well as how PLI can be included in this journey.

The fourth industrial revolution is expected to bring substantial changes to how maintenance will... more The fourth industrial revolution is expected to bring substantial changes to how maintenance will be conducted in the upcoming years. In this paper three main areas of technology innovation related to how Industry 4.0 can change maintenance and asset management have been identified: smart maintenance, smart working and smart products. However, implementing new technology is only part of the picture, and several resent papers have pointed to the importance of organizational factors. But it is also important to include economic factors when developing strategies to implement Industry 4.0 in maintenance and asset management. In this paper a model that does just that is proposed. This is done by utilizing a concept called Economic Value Added (EVA) and a more recent offspring in the domain of maintenance and asset management labeled Value Driven Maintenance (VDM) sensitivity analysis. An example of how the recent technology development in combination with economic preconditions can be u...

Advanced Manufacturing and Automation VIII, 2018

To stay competitive in the future, industrialists must be prepared to adopt the imminent changes ... more To stay competitive in the future, industrialists must be prepared to adopt the imminent changes and new technologies associated with Industrie 4.0. These changes apply equally to the field of maintenance, which is also developing quickly. Sensors, along with analyses and competence, are one of the most critical factors for Industrie 4.0 as they are the connectors between the digital and physical world. Utilization of these sensors within maintenance is a relatively unexplored field. Thus, the aim of this paper is to present a novel concept for ways sensor management can be linked to maintenance and thereby improve operational availability. The paper also presents an overview of sensor management and trends within maintenance.

Maintenance has traditionally been seen as a costly and unwanted evil. Nowadays, the view of main... more Maintenance has traditionally been seen as a costly and unwanted evil. Nowadays, the view of maintenance has changed, as new maintenance technologies and Smart Maintenance have proven to give competitive advantages for industrialists. Additionally, increased global competition and need for improving manufacturing performance has resulted in more focus on company’s maintenance function. Another field of interest, is how modern value chains can support the maintenance function in a company. Research on the field of value chain and maintenance has mainly been carried out independently, and research on how these two fields can be combined and utilized to strengthen each other seem to have just launched the start line. This is especially true when it comes to the area of improving maintenance programs, which traditionally have been static, inflexible, and inefficient. Thus, the aim of this paper is therefore to investigate on how maintenance programs can benefit from including a value ch...

Proceedings of the 6th International Workshop of Advanced Manufacturing and Automation, 2016

This paper is focused on how principles from Industry 4.0 in manufacturing can be used in operati... more This paper is focused on how principles from Industry 4.0 in manufacturing can be used in operation and maintenance of subsea production systems. The primary purpose and goal of the paper is to investigate the application of Smart Maintenance to achieve high level of safety, availability and profit in operation and maintenance of subsea production systems. The paper describes state-of-the-art in Smart Maintenance. This includes the framework for intelligent predictive maintenance, use of artificial intelligence for condition monitoring purposes and the progression of technologies for Smart Maintenance. The procedures for maintenance of Ormen Lange subsea choke modules are outlined. The paper investigates the performance of procedures for maintenance of Ormen Lange subsea choke modules, as compared to state-of-the-art in Smart Maintenance.The results are presented, as well a short conclusion. Suggestion for further work includes performing a quantitative Life Cycle Profit (LCP) analysis to investigate return on investment for further implementation of Smart Maintenance for Ormen Lange subsea choke modules.

Safety and Reliability – Safe Societies in a Changing World, Jun 15, 2018

With the onset of Industry 4.0 several technological possibilities are offered in industry such a... more With the onset of Industry 4.0 several technological possibilities are offered in industry such as big data analytics, digital twin and augmented reality. The result is a more digitalised industry where faster and better decisions are possible. In long term this should provide a more reliable production with increased plant capacity and reduced downtime. To succeed with these possibilities a Cyber Physical Systems (CPS) must be established for the company. Currently, an own framework for CPS is under development and is expected to be tailored for Norwegian manufacturing. When building on the principle in Industry 4.0, big data capability with machine learning will be a fundamental model. Nevertheless, Industry 4.0 should also include other models for big data capability such as reliability modelling. The aim in this article is to present the current status of CPS framework and how it could be implemented in manufacturing industries. In particular, the article discusses and demonstrates the balance between machine learning and reliability engineering in big data analytics.

Proceedings of the 6th International Workshop of Advanced Manufacturing and Automation, 2016

With the current situation of high demand of sustainable manufacturing, different stakeholders ha... more With the current situation of high demand of sustainable manufacturing, different stakeholders have clear expectations for more environmental manufacturing and at the same time minimizing the operational costs. The role of maintenance plays a key role in the path towards sustainable manufacturing. For achieving green manufacturing, more datadriven predictive maintenance strategies is needed and is expected to reduce energy consumption, maintenance resources in terms of spare parts, and reduction of consumables in terms of example lubrication. The overall bottom-line for the predictive maintenance strategy is increased availability, reduction of maintenance hours in terms of reactive maintenance activities, and increased profit for the manufacturing business. For a predictive maintenance strategy, it is crucial to develop Key Performance Indicators (KPIs) for the maintenance management. Today, common KPIs such as availability and different indicators for maintenance cost has been developed. When aiming for more green manufacturing, a more integrated application of maintenance KPIs are needed. Today, the KPI Profit Loss Indicator (PLI) has been developed and demonstrated in the saw mill industry and is regarded to support a more integrated approach in terms of Integrated Planning (IPL). The aim of this article is develop a structured approach for data-driven predictive maintenance aligned with the concept of PLI. Through a case study, the approach is partly demonstrated for the manufacturing industry. The results in this demonstration shows that the data-driven maintenance strategy will have a positive impact of the PLI value and provide a sustainable manufacturing in long-term.

Proceedings of the 6th International Workshop of Advanced Manufacturing and Automation, 2016

This abstract is an introduction to the next generation of High Performance Industrial Manufactur... more This abstract is an introduction to the next generation of High Performance Industrial Manufacturing, through the Industry standard 4.0. The fourth Industrial standard is based on advanced Automation and Robotics, sensor based computer technology, interconnected by wireless communication, and supported by BIG Data solutions. Effective management and human cooperation i.e. teamwork and SUM© processes will be increasingly important in the future. This paper also focuses on the new industrial standard in relation to OEE (Overall Equipment Effectiveness), Predictive Maintenance and total performance related to all equipment in the industrial factory processes. Not a few highly automated machines, but the system as whole. OEE is a well-known standardized tool for performance measurement throughout the industry. In order to utilize data systems as ERP (Enterprise Resource Planning) and PLM (engineering systems), they must be integrated with business systems. Management normally acts on the bases of facts and financial performance. In most companies increased profit is the overall goal. Future management systems aim for a fully integrated and automated data flow based on advanced sensor technology. Increased use of digital systems enables quicker and better decisions. Refers to previous paper "High Performance Innovative teams (IWAMA 2010).

Advanced Manufacturing and Automation VII, 2018

With the immense pressure to sustain competitive in European manufacturing, the strategy of digit... more With the immense pressure to sustain competitive in European manufacturing, the strategy of digitalizing in this industry sector is indeed necessary. With the onset of new ICT technology and big data capabilities, the physical asset and data computation is integrated in manufacturing through Cyber Physical Systems (CPS). This strategy also denoted as Industry 4.0 will also improve the maintenance function significantly in manufacturing. In particular, maintenance planning will be more synchronized in production scheduling. The aim of this article is to develop an integrated planning (IPL) approach that synchronizes production and maintenance planning with predictive maintenance capability. The result in this article is based on a case study and simulation of manufacturing equipment. In particular, application of key performance indicators (KPIs) is shown to be essential when running the synchronizing mechanism in IPL. The scientific application of the case study is alignment of the IPL theory and new approach in maintenance planning. Furthermore, the application to practice is improved maintenance planning in IPL that increases a reliable plant capacity. It is concluded that the IPL approach should be considered to be a generic platform for manufacturing industry that should be demonstrated further in other manufacturing branches in Europe.

WIT transactions on engineering sciences, 2016

With the challenges of “silo thinking” in production and manufacturing, several disciplines and d... more With the challenges of “silo thinking” in production and manufacturing, several disciplines and departments perform activities that affect each other, which can lead to suboptimal results in production with respect to extra costs and lack of production assurance. For maintenance management, silo thinking may result in unplanned maintenance activities, which may impede production plans. As a remedy to avoid this challenge, a key performance indicator (KPI) for maintenance management has been developed and is denoted as profit loss indicator (PLI). The purpose of this research was to investigate how this indicator can be further developed with more perspectives of concepts of Toyota Production System and Six Sigma. In particular, this PLI is evaluated for a relevant example in the industry with a case study. Results from both literature and case study are used to build further on the PLI concept.

Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems

Advances in Manufacturing

With the emergence of Industry 4.0, maintenance is considered to be a specific area of action tha... more With the emergence of Industry 4.0, maintenance is considered to be a specific area of action that is needed to successfully sustain a competitive advantage. For instance, predictive maintenance will be central for asset utilization, service, and after-sales in realizing Industry 4.0. Moreover, artificial intelligence (AI) is also central for Industry 4.0, and offers data-driven methods. The aim of this article is to develop a new maintenance model called deep digital maintenance (DDM). With the support of theoretical foundations in cyber-physical systems (CPS) and maintenance, a concept for DDM is proposed. In this paper, the planning module of DDM is investigated in more detail with realistic industrial data from earlier case studies. It is expected that this planning module will enable integrated planning (IPL) where maintenance and production planning can be more integrated. The result of the testing shows that both the remaining useful life (RUL) and the expected profit loss indicator (PLI) of ignoring the failure can be calculated for the planning module. The article concludes that further research is needed in testing the accuracy of RUL, classifying PLI for different failure modes, and testing of other DDM modules with industrial case studies.

Journal of Quality in Maintenance Engineering

Purpose -The aim of this article is to develop a novel model for maintenance backlog of physical ... more Purpose -The aim of this article is to develop a novel model for maintenance backlog of physical assets and structure it in a framework for Integrated Planning.

Lecture Notes in Mechanical Engineering, 2016

Advanced Materials Research, Nov 26, 2014