artificial intelligence blockchain building energy management building information modelling data analytics data mining energy efficiency Energy efficient building energy management energy performance indicator flexibility measurement industry 4.0 industry 4.0 maturity assessment Internet of Things knowledge management linked data machine learning manufacturing Ontology ontology engineering ontology population product configuration product lifecycle management production planning and control requirement engineering resource efficient manufacturing smart cities Supply Chain 4.0 sustainability virtual engineering
2023 |
Krstevski Stefan; Fatahi Valilai, Omid; Wicaksono Hendro In Proceedings of the 2023 10th International Conference on Industrial Engineering and Applications (ICIEAEU '23), pp. 98–106, Association for Computing Machinery, New York, NY, USA, 2023. Abstract | Links | BibTeX | Tags: energy efficiency, manufacturing, operation research, production planning and control, production scheduling, sustainability @inproceedings{Krstevski2023, title = {Integrating Real-Time Dynamic Electricity Price Forecast into Job Shop Production Scheduling Model with Multiple Machine Environments}, author = {Krstevski, Stefan; Fatahi Valilai, Omid; Wicaksono, Hendro }, url = {https://doi.org/10.1145/3587889.3587905}, doi = {10.1145/3587889.3587905}, year = {2023}, date = {2023-06-09}, booktitle = {In Proceedings of the 2023 10th International Conference on Industrial Engineering and Applications (ICIEAEU '23)}, pages = {98–106}, publisher = {Association for Computing Machinery, New York, NY, USA}, abstract = {One of the challenges in the transition towards green electricity is the intermittence of power generated by renewable sources. Thus, power consumers, including the manufacturing industry, must adapt their activities and processes to green electricity supply. Real-time dynamic pricing is an approach to encourage electricity consumers to change their consumption patterns by lowering prices when the availability of green electricity in the grid is high. Due to the introduction of real-time electricity pricing, manufacturing companies must adapt their production planning by integrating dynamic price information into their production scheduling. Our research focuses on extending the basic production scheduling mathematical model by introducing real-time power pricing in the model. The prices are built based on the current proportion of green electricity in the grid represented in the green electricity index (GEI) with one-hour intervals. This paper also illustrates a scenario of how to use the model. Our future research will further extend the model addressing the flexibility of manufacturing shop floors (e.g. adding buffer, retooling, and setup time) and validate the model in two small and medium manufacturing enterprises.}, keywords = {energy efficiency, manufacturing, operation research, production planning and control, production scheduling, sustainability}, pubstate = {published}, tppubtype = {inproceedings} } One of the challenges in the transition towards green electricity is the intermittence of power generated by renewable sources. Thus, power consumers, including the manufacturing industry, must adapt their activities and processes to green electricity supply. Real-time dynamic pricing is an approach to encourage electricity consumers to change their consumption patterns by lowering prices when the availability of green electricity in the grid is high. Due to the introduction of real-time electricity pricing, manufacturing companies must adapt their production planning by integrating dynamic price information into their production scheduling. Our research focuses on extending the basic production scheduling mathematical model by introducing real-time power pricing in the model. The prices are built based on the current proportion of green electricity in the grid represented in the green electricity index (GEI) with one-hour intervals. This paper also illustrates a scenario of how to use the model. Our future research will further extend the model addressing the flexibility of manufacturing shop floors (e.g. adding buffer, retooling, and setup time) and validate the model in two small and medium manufacturing enterprises. |
2020 |
Bai Xuqi; Wicaksono, Hendro How Relevant Are Environmental Factors in The Ergonomic Performance Assessments? Journal Article Procedia Manufacturing, 52 , pp. 325-330, 2020. Abstract | Links | BibTeX | Tags: ergonomics, manufacturing, resource efficient manufacturing @article{Wicaksono2020c, title = {How Relevant Are Environmental Factors in The Ergonomic Performance Assessments?}, author = {Bai, Xuqi; Wicaksono, Hendro }, url = {https://doi.org/10.1016/j.promfg.2020.11.054}, doi = {10.1016/j.promfg.2020.11.054}, year = {2020}, date = {2020-12-31}, journal = {Procedia Manufacturing}, volume = {52}, pages = {325-330}, abstract = {A suitable working environment is crucial to ensure the worker’s safety and health, results in higher productivity in production systems. As one of the most important elements of production, the assembly processes require the most human involvement. However, researches on ergonomics in assembly systems focus merely on task-related physical factors such as action forces, posture, movement, task repetition, etc. This paper aims to investigate the relevance of environmental measures of temperature, humidity, ventilation, noise, lighting, and cleanness to the assembly workers, and the relative importance of environmental factors in comparison with the task-related physical factors. A survey was conducted among 20 assembly workers and engineers in the hope to realize the urgency to integrate environmental characteristics into routinely conducted ergonomic performance assessments.}, keywords = {ergonomics, manufacturing, resource efficient manufacturing}, pubstate = {published}, tppubtype = {article} } A suitable working environment is crucial to ensure the worker’s safety and health, results in higher productivity in production systems. As one of the most important elements of production, the assembly processes require the most human involvement. However, researches on ergonomics in assembly systems focus merely on task-related physical factors such as action forces, posture, movement, task repetition, etc. This paper aims to investigate the relevance of environmental measures of temperature, humidity, ventilation, noise, lighting, and cleanness to the assembly workers, and the relative importance of environmental factors in comparison with the task-related physical factors. A survey was conducted among 20 assembly workers and engineers in the hope to realize the urgency to integrate environmental characteristics into routinely conducted ergonomic performance assessments. |
Angreani Linda Salma; Vijaya, Annas; Wicaksono Hendro Systematic Literature Review of Industry 4.0 Maturity Model for Manufacturing and Logistics Sectors Journal Article Procedia Manufacturing, 52 , 2020. Abstract | Links | BibTeX | Tags: industry 4.0, industry 4.0 maturity assessment, manufacturing, systematic literature review @article{Angreani2020, title = {Systematic Literature Review of Industry 4.0 Maturity Model for Manufacturing and Logistics Sectors}, author = {Angreani, Linda Salma; Vijaya, Annas; Wicaksono, Hendro}, url = {https://doi.org/10.1016/j.promfg.2020.11.056}, doi = {doi.org/10.1016/j.promfg.2020.11.056}, year = {2020}, date = {2020-12-31}, journal = {Procedia Manufacturing}, volume = {52}, abstract = {A maturity model is a wide technique to measure several aspects and identify the current state of processes in an organization, which can be used as a starting point for business improvement. In the Industry 4.0 context, several terms are used to express the model, such as readiness assessment model, roadmap, framework, and maturity index. They have the same purpose of measuring how the current state of an organization unit is capable of adopting and implementing the concept of industry 4.0 in the future. Many researchers had proposed maturity models for assessing Industry 4.0 readiness and maturity since 2011 when Industry 4.0 was commenced. However, there has been no attempt to analyze empirical evidence systematically. This paper aims to analyze currently available maturity models related to Industry 4.0 and provide a synthesis on those maturity models. This paper describes a systematic literature review (SLR) of empirical studies implemented on the maturity model published in several reputable and relevant sources. It focuses on the manufacturing and logistics sectors since the processes in both sectors can be highly improved through the introduction of technologies such as cyber-physical systems, internet of things, and artificial intelligence. In general, the primary purpose of the review is to address the following questions: (1) Based on what dimensions do researchers develop Industry 4.0 maturity models, and what are the most used and influencing parameters in those dimensions? (2) How do those maturity models compare to each other in terms of dimension complexity, techniques, maturity leveling, and kind of application sectors of the model? In conclusion, the maturity model in the context of Industry 4.0 is promising to guide the adoption of industry 4.0 technologies at the organization level. However, just having a maturity model is not enough. More efforts are needed to facilitate the application of it.}, keywords = {industry 4.0, industry 4.0 maturity assessment, manufacturing, systematic literature review}, pubstate = {published}, tppubtype = {article} } A maturity model is a wide technique to measure several aspects and identify the current state of processes in an organization, which can be used as a starting point for business improvement. In the Industry 4.0 context, several terms are used to express the model, such as readiness assessment model, roadmap, framework, and maturity index. They have the same purpose of measuring how the current state of an organization unit is capable of adopting and implementing the concept of industry 4.0 in the future. Many researchers had proposed maturity models for assessing Industry 4.0 readiness and maturity since 2011 when Industry 4.0 was commenced. However, there has been no attempt to analyze empirical evidence systematically. This paper aims to analyze currently available maturity models related to Industry 4.0 and provide a synthesis on those maturity models. This paper describes a systematic literature review (SLR) of empirical studies implemented on the maturity model published in several reputable and relevant sources. It focuses on the manufacturing and logistics sectors since the processes in both sectors can be highly improved through the introduction of technologies such as cyber-physical systems, internet of things, and artificial intelligence. In general, the primary purpose of the review is to address the following questions: (1) Based on what dimensions do researchers develop Industry 4.0 maturity models, and what are the most used and influencing parameters in those dimensions? (2) How do those maturity models compare to each other in terms of dimension complexity, techniques, maturity leveling, and kind of application sectors of the model? In conclusion, the maturity model in the context of Industry 4.0 is promising to guide the adoption of industry 4.0 technologies at the organization level. However, just having a maturity model is not enough. More efforts are needed to facilitate the application of it. |
2014 |
Wicaksono, Hendro; Jost, Fabian; Rogalski, Sven; Ovtcharova, Jivka Energy efficiency evaluation in manufacturing through an ontology-represented knowledge base Journal Article Intelligent Systems in Accounting, Finance and Management, 21 (1), pp. 59-69, 2014. Abstract | Links | BibTeX | Tags: energy efficiency, knowledge base, knowledge management, manufacturing, Ontology @article{Wicaksono2014, title = {Energy efficiency evaluation in manufacturing through an ontology-represented knowledge base}, author = {Hendro Wicaksono and Fabian Jost and Sven Rogalski and Jivka Ovtcharova}, url = {http://onlinelibrary.wiley.com/doi/10.1002/isaf.1347/abstract}, doi = {10.1002/isaf.1347}, year = {2014}, date = {2014-04-01}, journal = {Intelligent Systems in Accounting, Finance and Management}, volume = {21}, number = {1}, pages = {59-69}, abstract = {Improving energy efficiency in a manufacturing company through an energy management system requires active participation of different stakeholders and involvement of different organizational entities and technical processes. Interoperability of stakeholders and entities is the key factor to achieve a successful implementation of an energy management system. Researchers have been developing approaches in applying ontologies to address interoperability issues among humans as well as machines. Ontologies have also been used for knowledge representation in different domains, such as energy management and manufacturing. In recent years, researchers have developed knowledge-based intelligent energy management systems in buildings, especially households, which use ontologies for knowledge representation. In the manufacturing domain, ontologies have been used for knowledge management in order to provide a common formal understanding between the stakeholders, who have different background knowledge. This paper proposes an approach to apply ontology to allow knowledge-based energy efficiency evaluation in manufacturing companies. The ontology provides a formal knowledge representation that addresses the interoperability issues due to different human stakeholders as well as machines involved in the energy management system of the company. This paper also describes the methods used to construct and to process the ontology. }, keywords = {energy efficiency, knowledge base, knowledge management, manufacturing, Ontology}, pubstate = {published}, tppubtype = {article} } Improving energy efficiency in a manufacturing company through an energy management system requires active participation of different stakeholders and involvement of different organizational entities and technical processes. Interoperability of stakeholders and entities is the key factor to achieve a successful implementation of an energy management system. Researchers have been developing approaches in applying ontologies to address interoperability issues among humans as well as machines. Ontologies have also been used for knowledge representation in different domains, such as energy management and manufacturing. In recent years, researchers have developed knowledge-based intelligent energy management systems in buildings, especially households, which use ontologies for knowledge representation. In the manufacturing domain, ontologies have been used for knowledge management in order to provide a common formal understanding between the stakeholders, who have different background knowledge. This paper proposes an approach to apply ontology to allow knowledge-based energy efficiency evaluation in manufacturing companies. The ontology provides a formal knowledge representation that addresses the interoperability issues due to different human stakeholders as well as machines involved in the energy management system of the company. This paper also describes the methods used to construct and to process the ontology. |
2013 |
Wicaksono, Hendro; Aleksandrov, Kiril; Rogalski, Sven; Ovtcharova, Jivka An ICT Supported Holistic Approach for Qualitative and Quantitative Energy Efficiency Evaluation in Manufacturing Company Inproceedings Emmanouilidis, Christos; Taisch, Marco; Kiritsis, Dimitris (Ed.): Advances in Production Management Systems. Competitive Manufacturing for Innovative Products and Services, pp. 25-32, Springer Berlin Heidelberg, Berlin, Heidelberg, 2013, ISBN: 978-3-642-40352-1. Abstract | Links | BibTeX | Tags: energy performance indicator, manufacturing @inproceedings{Wicaksono2013, title = {An ICT Supported Holistic Approach for Qualitative and Quantitative Energy Efficiency Evaluation in Manufacturing Company}, author = {Hendro Wicaksono and Kiril Aleksandrov and Sven Rogalski and Jivka Ovtcharova}, editor = {Christos Emmanouilidis and Marco Taisch and Dimitris Kiritsis}, url = {https://link.springer.com/chapter/10.1007/978-3-642-40352-1_4}, doi = {10.1007/978-3-642-40352-1_4}, isbn = {978-3-642-40352-1}, year = {2013}, date = {2013-12-03}, booktitle = {Advances in Production Management Systems. Competitive Manufacturing for Innovative Products and Services}, pages = {25-32}, publisher = {Springer Berlin Heidelberg}, address = {Berlin, Heidelberg}, abstract = {The global climate change and the rising of energy prices force manufacturing companies to regulate their energy usage. A suitable step to achieve that is the introduction of energy management. This paper presents an ICT based holistic approach to help manufacturing companies in the implementation of energy management system. It consists of methods to support quantitative and qualitative energy efficiency evaluation of their operations. The approach uses an ontological knowledge base containing the structures and rules representing best practices as reference of energy efficiency to support the qualitative evaluation. In the approach, we also develop measurement figures called Energy Performance Indices (EPI) to determine the energy efficiency degrees in different organizational parts of the company. The paper also describes the application of the approach in a small medium sized manufacturer.}, keywords = {energy performance indicator, manufacturing}, pubstate = {published}, tppubtype = {inproceedings} } The global climate change and the rising of energy prices force manufacturing companies to regulate their energy usage. A suitable step to achieve that is the introduction of energy management. This paper presents an ICT based holistic approach to help manufacturing companies in the implementation of energy management system. It consists of methods to support quantitative and qualitative energy efficiency evaluation of their operations. The approach uses an ontological knowledge base containing the structures and rules representing best practices as reference of energy efficiency to support the qualitative evaluation. In the approach, we also develop measurement figures called Energy Performance Indices (EPI) to determine the energy efficiency degrees in different organizational parts of the company. The paper also describes the application of the approach in a small medium sized manufacturer. |
Wicaksono, Hendro; Belzner, Tim; Ovtcharova, Jivka Efficient Energy Performance Indicators for Different Level of Production Organizations in Manufacturing Companies Inproceedings Prabhu, Vittal; Taisch, Marco; Kiritsis, Dimitris (Ed.): Advances in Production Management Systems. Sustainable Production and Service Supply Chains, pp. 249-256, Springer Berlin Heidelberg, Berlin, Heidelberg, 2013, ISBN: 978-3-642-41266-0. Abstract | Links | BibTeX | Tags: energy efficiency, energy performance indicator, manufacturing @inproceedings{Wicaksono2013c, title = {Efficient Energy Performance Indicators for Different Level of Production Organizations in Manufacturing Companies}, author = {Hendro Wicaksono and Tim Belzner and Jivka Ovtcharova}, editor = {Vittal Prabhu and Marco Taisch and Dimitris Kiritsis}, url = {https://link.springer.com/book/10.1007/978-3-642-41266-0}, doi = {10.1007/978-3-642-41266-0_31}, isbn = {978-3-642-41266-0}, year = {2013}, date = {2013-09-12}, booktitle = {Advances in Production Management Systems. Sustainable Production and Service Supply Chains}, volume = {414}, pages = {249-256}, publisher = {Springer Berlin Heidelberg}, address = {Berlin, Heidelberg}, series = {IFIP}, abstract = {Demands for lower CO2 emissions due to the climate change and the rising of energy prices force manufacturing companies to deal with the energy issue. Energy management, where one of the tasks is energy efficiency evaluation, can help the companies to overcome the issue. This paper presents holistic metric to evaluate the energy efficiency in manufacturing companies, which considers the different organization level of production, such as machine or equipment level, production line level, and factory level. As the size of the scope and the number of observed factors vary, the metric provide flexible criteria to select relevant variables. The developed metric could be used to simulate and to compare energy efficiency of different production facilities, lines, and factories in a single company. The metric is an instrument to recognize how energy (in) efficient is a production system, so that adjustments may be made in the planning and management to achieve the energy savings.}, keywords = {energy efficiency, energy performance indicator, manufacturing}, pubstate = {published}, tppubtype = {inproceedings} } Demands for lower CO2 emissions due to the climate change and the rising of energy prices force manufacturing companies to deal with the energy issue. Energy management, where one of the tasks is energy efficiency evaluation, can help the companies to overcome the issue. This paper presents holistic metric to evaluate the energy efficiency in manufacturing companies, which considers the different organization level of production, such as machine or equipment level, production line level, and factory level. As the size of the scope and the number of observed factors vary, the metric provide flexible criteria to select relevant variables. The developed metric could be used to simulate and to compare energy efficiency of different production facilities, lines, and factories in a single company. The metric is an instrument to recognize how energy (in) efficient is a production system, so that adjustments may be made in the planning and management to achieve the energy savings. |
Rogalski, Sven; Wicaksono, Hendro; Krahtov, Konstantin Resource-Efficient Production Planning through Flexibility Measurements in Value Creation Systems Inproceedings Prabhu, Vittal; Taisch, Marco; Kiritsis, Dimitris (Ed.): Advances in Production Management Systems. Sustainable Production and Service Supply Chains, Springer Berlin Heidelberg, Berlin, Heidelberg, 2013, ISBN: 978-3-642-41266-0. Abstract | Links | BibTeX | Tags: flexibility measurement, manufacturing, production planning and control, resource efficiency @inproceedings{Rogalski2013, title = {Resource-Efficient Production Planning through Flexibility Measurements in Value Creation Systems}, author = {Sven Rogalski and Hendro Wicaksono and Konstantin Krahtov}, editor = {Vittal Prabhu and Marco Taisch and Dimitris Kiritsis}, url = {https://link.springer.com/chapter/10.1007/978-3-642-41266-0_15}, doi = {10.1007/978-3-642-41266-0_15}, isbn = {978-3-642-41266-0}, year = {2013}, date = {2013-09-12}, booktitle = {Advances in Production Management Systems. Sustainable Production and Service Supply Chains}, volume = {414}, publisher = {Springer Berlin Heidelberg}, address = {Berlin, Heidelberg}, abstract = {For years, manufacturing companies have faced an increasingly complex and rapidly changing market environment which is the result of, if nothing else, higher customer individualization. This particularly concerns SME's, whose competitiveness is increasingly dependent on the early identification of new customer and market requirements and their ability to dynamically respond to these in an adequate fashion. In order to meet the high standards demanded of the planning quality and planning safety with ever increasing complexity and the continuous reduction of the planning time available, SME-compatible IT technologies are needed for the simulation of complex manufacturing relations. The following article addresses this problem and in-troduces the method set ecoFLEX, which enables the simulation of targeted and dynamic alignment of existing plant structures, resources and value-added processes with new production requirements. Unlike digital factory planning tools, a complete picture of the specific plant situation is not required, as will be illustrated by selected case studies from the medium sized production sector.}, keywords = {flexibility measurement, manufacturing, production planning and control, resource efficiency}, pubstate = {published}, tppubtype = {inproceedings} } For years, manufacturing companies have faced an increasingly complex and rapidly changing market environment which is the result of, if nothing else, higher customer individualization. This particularly concerns SME's, whose competitiveness is increasingly dependent on the early identification of new customer and market requirements and their ability to dynamically respond to these in an adequate fashion. In order to meet the high standards demanded of the planning quality and planning safety with ever increasing complexity and the continuous reduction of the planning time available, SME-compatible IT technologies are needed for the simulation of complex manufacturing relations. The following article addresses this problem and in-troduces the method set ecoFLEX, which enables the simulation of targeted and dynamic alignment of existing plant structures, resources and value-added processes with new production requirements. Unlike digital factory planning tools, a complete picture of the specific plant situation is not required, as will be illustrated by selected case studies from the medium sized production sector. |
Wicaksono, Hendro; Prohl, Enrst Victor; Ovtcharova, Jivka Hyper heuristc based production process scheduling to improve productivity in sustainable manufacturing Inproceedings Proceeding the 22nd International Conference on Production Research, Brazil, 28 July – 1 August, 2013, 2013. Abstract | BibTeX | Tags: energy efficiency, hyper heuristics, manufacturing, production scheduling @inproceedings{Wicaksono2013d, title = {Hyper heuristc based production process scheduling to improve productivity in sustainable manufacturing}, author = {Hendro Wicaksono and Enrst Victor Prohl and Jivka Ovtcharova}, year = {2013}, date = {2013-08-01}, booktitle = {Proceeding the 22nd International Conference on Production Research, Brazil, 28 July – 1 August, 2013}, abstract = {In recent years, increased customer-demand in individualized and timely products has changed the playing field for manufacturing industries. The production process is perpetually gaining complexity whereas its life-cycle is shortening. Additionally, a growing ecological conscience enforces the consideration of energy effi-ciency. Intelligent production process scheduling is a core instrument to increase efficiency of the value-added chain whilst acknowledging existing constraints. This paper introduces a hyper-heuristic based framework for production scheduling that incorporates economic and ecological aspects. In contrast to meta heuristics that aim for easily reusable solution-methods to NP-Hard scheduling problems, hyper-heuristics try to automate the search for the best solution methods. Thus a hyper-heuristic does not seek for the best solution, but for a heuristic that solves the problem best. Other than conventional scheduling described in lit-erature, the proposed approach in this paper copes with many aspects (constraints and objectives) at once, such as retooling activities, energy efficiency, energy peak load avoidance, product lot size, operation multi-plicity, and shift work. Furthermore, this paper will introduce the incorporation possibilities of prior knowledge coming from both human and machine learning (data mining) into the hyper-heuristic framework. }, keywords = {energy efficiency, hyper heuristics, manufacturing, production scheduling}, pubstate = {published}, tppubtype = {inproceedings} } In recent years, increased customer-demand in individualized and timely products has changed the playing field for manufacturing industries. The production process is perpetually gaining complexity whereas its life-cycle is shortening. Additionally, a growing ecological conscience enforces the consideration of energy effi-ciency. Intelligent production process scheduling is a core instrument to increase efficiency of the value-added chain whilst acknowledging existing constraints. This paper introduces a hyper-heuristic based framework for production scheduling that incorporates economic and ecological aspects. In contrast to meta heuristics that aim for easily reusable solution-methods to NP-Hard scheduling problems, hyper-heuristics try to automate the search for the best solution methods. Thus a hyper-heuristic does not seek for the best solution, but for a heuristic that solves the problem best. Other than conventional scheduling described in lit-erature, the proposed approach in this paper copes with many aspects (constraints and objectives) at once, such as retooling activities, energy efficiency, energy peak load avoidance, product lot size, operation multi-plicity, and shift work. Furthermore, this paper will introduce the incorporation possibilities of prior knowledge coming from both human and machine learning (data mining) into the hyper-heuristic framework. |
Rogalski, Sven; Siebel, Jan; Wicaksono, Hendro Resource efficient planning and operation of production system using IT-supported flexibility management Inproceedings Proceeding the 22nd International Conference on Production Research, Brazil, 28 July – 1 August, 2013, 2013. Abstract | BibTeX | Tags: manufacturing, manufacturing flexibility, production planning and control, resource efficiency, resource efficient manufacturing, SME oriented technology @inproceedings{Rogalski2013b, title = {Resource efficient planning and operation of production system using IT-supported flexibility management}, author = {Sven Rogalski and Jan Siebel and Hendro Wicaksono}, year = {2013}, date = {2013-08-01}, booktitle = {Proceeding the 22nd International Conference on Production Research, Brazil, 28 July – 1 August, 2013}, abstract = {For years, manufacturing companies have faced an increasingly complex and rapidly changing market environment which is the result of, if nothing else, higher customer individualization. This particularly concerns SME’s, whose competitiveness is increasingly dependent on the early identification of new customer and market requirements and their ability to dynamically respond to these in an adequate fashion. In order to meet the high standards demanded of the planning quality and planning safety with ever increasing complexity and the continuous reduction of the planning time available, SME-compatible IT technologies are needed for the simulation of complex manufacturing relations. The following article addresses this problem and introduces the method set ecoFLEX, which enables the simulation of targeted and dynamic alignment of existing plant structures, resources and value-added processes with new production requirements. Unlike digital factory planning tools, a complete picture of the specific plant situation is not required, as will be illustrated by selected case studies from the medium sized production sector.}, keywords = {manufacturing, manufacturing flexibility, production planning and control, resource efficiency, resource efficient manufacturing, SME oriented technology}, pubstate = {published}, tppubtype = {inproceedings} } For years, manufacturing companies have faced an increasingly complex and rapidly changing market environment which is the result of, if nothing else, higher customer individualization. This particularly concerns SME’s, whose competitiveness is increasingly dependent on the early identification of new customer and market requirements and their ability to dynamically respond to these in an adequate fashion. In order to meet the high standards demanded of the planning quality and planning safety with ever increasing complexity and the continuous reduction of the planning time available, SME-compatible IT technologies are needed for the simulation of complex manufacturing relations. The following article addresses this problem and introduces the method set ecoFLEX, which enables the simulation of targeted and dynamic alignment of existing plant structures, resources and value-added processes with new production requirements. Unlike digital factory planning tools, a complete picture of the specific plant situation is not required, as will be illustrated by selected case studies from the medium sized production sector. |
2012 |
Rogalski, Sven; Siebel, Jan; Aleksandrov, Kiril; Wicaksono, Hendro Sustainable Production Planning Through Flexibility Measurements In Different Manufacturing Organizational Levels Inproceedings Proceeding 10th Global Conference of Sustainable Manufacturing (GCSM), 2012. Abstract | BibTeX | Tags: change management, digital factory, flexibility measurement, manufacturing, resource efficient manufacturing @inproceedings{Rogalski2012, title = {Sustainable Production Planning Through Flexibility Measurements In Different Manufacturing Organizational Levels}, author = {Sven Rogalski and Jan Siebel and Kiril Aleksandrov and Hendro Wicaksono}, year = {2012}, date = {2012-11-02}, booktitle = {Proceeding 10th Global Conference of Sustainable Manufacturing (GCSM)}, abstract = {Production companies operate in increasingly turbulent and discontinuous environments. The rapid speed of change, coupled with a high complexity of cause-effect relationships of industries, globally-dispersed markets, technologies and economic areas create great challenges to the manufacturing systems. Therefore, a more holistic view of technical and organizational freedom is needed in production to support sustainable planning, control and modification of manufacturing systems, which incorporate system and life cycle aspects to the goal of profitability. Hence, reliable statements about flexibility on different organisational levels in a manufacturing system have a considerable role to ensure resource efficiency. The following paper details the concept for calculating the production flexibility and the application experience in industrial production from the flexibility assessment toolbox ecoFLEX. It enables the simulation of targeted and dynamic alignment of existing plant structures and value-added processes with external environmental and internal changes. Unlike digital factory planning tools, a complete picture of the specific plant situation is not required, as will be illustrated by selected case studies from the medium sized assembling and stamping production enterprises. }, keywords = {change management, digital factory, flexibility measurement, manufacturing, resource efficient manufacturing}, pubstate = {published}, tppubtype = {inproceedings} } Production companies operate in increasingly turbulent and discontinuous environments. The rapid speed of change, coupled with a high complexity of cause-effect relationships of industries, globally-dispersed markets, technologies and economic areas create great challenges to the manufacturing systems. Therefore, a more holistic view of technical and organizational freedom is needed in production to support sustainable planning, control and modification of manufacturing systems, which incorporate system and life cycle aspects to the goal of profitability. Hence, reliable statements about flexibility on different organisational levels in a manufacturing system have a considerable role to ensure resource efficiency. The following paper details the concept for calculating the production flexibility and the application experience in industrial production from the flexibility assessment toolbox ecoFLEX. It enables the simulation of targeted and dynamic alignment of existing plant structures and value-added processes with external environmental and internal changes. Unlike digital factory planning tools, a complete picture of the specific plant situation is not required, as will be illustrated by selected case studies from the medium sized assembling and stamping production enterprises. |
Wicaksono, Hendro; Rogalski, Sven; Ovtcharova, Jivka Ontology Driven Approach for Intelligent Energy Management in Discrete Manufacturing Inproceedings Proceedings of the International Conference on Knowledge Engineering and Ontology Development, pp. 108-114, INSTICC SciTePress, 2012, ISBN: 978-989-8565-30-3. Abstract | Links | BibTeX | Tags: energy efficiency, energy management, knowledge acquisition, knowledge capturing, machine learning, manufacturing, Ontology @inproceedings{Wicaksono2012c, title = {Ontology Driven Approach for Intelligent Energy Management in Discrete Manufacturing}, author = {Hendro Wicaksono and Sven Rogalski and Jivka Ovtcharova}, url = {http://www.scitepress.org/PublicationsDetail.aspx?ID=VdNAwL50fGw=&t=1}, doi = {10.5220/0004141601080114}, isbn = {978-989-8565-30-3}, year = {2012}, date = {2012-10-07}, booktitle = {Proceedings of the International Conference on Knowledge Engineering and Ontology Development}, volume = {1}, pages = {108-114}, publisher = {SciTePress}, organization = {INSTICC}, abstract = {In recent years ontologies have been used for knowledge representation in different domains, such as energy management and manufacturing. Researchers have developed approaches in applying ontologies for intelligent energy management in households. In the manufacturing domain, ontologies have been used for knowledge management in order to provide a common formal understanding between the stakeholders, who have different background knowledge. Energy management in a manufacturing company involves different organizational entities and technical processes. This paper proposes an approach to applying ontology for intelligent energy management in discrete manufacturing companies. The ontology provides a formal knowledge representation that is accessible by different human stakeholders as well as machines in the company. This paper also demonstrates the methods used to construct and to process the ontology.}, keywords = {energy efficiency, energy management, knowledge acquisition, knowledge capturing, machine learning, manufacturing, Ontology}, pubstate = {published}, tppubtype = {inproceedings} } In recent years ontologies have been used for knowledge representation in different domains, such as energy management and manufacturing. Researchers have developed approaches in applying ontologies for intelligent energy management in households. In the manufacturing domain, ontologies have been used for knowledge management in order to provide a common formal understanding between the stakeholders, who have different background knowledge. Energy management in a manufacturing company involves different organizational entities and technical processes. This paper proposes an approach to applying ontology for intelligent energy management in discrete manufacturing companies. The ontology provides a formal knowledge representation that is accessible by different human stakeholders as well as machines in the company. This paper also demonstrates the methods used to construct and to process the ontology. |
Rogalski, Sven; Wicaksono, Hendro Handling resource efficiency in production of small and medium sized enterprises Inproceedings 2012 18th International ICE Conference on Engineering, Technology and Innovation, pp. 1-9, IEEE, Munich, Germany, 2012. Abstract | Links | BibTeX | Tags: change management, flexibility measurement, Genetic algorithm, manufacturing, resource efficiency @inproceedings{Rogalski2012c, title = {Handling resource efficiency in production of small and medium sized enterprises}, author = {Sven Rogalski and Hendro Wicaksono}, url = {http://ieeexplore.ieee.org/document/6297707/}, doi = {10.1109/ICE.2012.6297707}, year = {2012}, date = {2012-09-10}, booktitle = {2012 18th International ICE Conference on Engineering, Technology and Innovation}, pages = {1-9}, publisher = {IEEE}, address = {Munich, Germany}, abstract = {For years, production companies have faced an increasingly complex and rapidly changing market, which results in higher client customization. These coupled with a high complexity of cause-effect relationships of industries, globally-dispersed markets, technologies and economic areas create great challenges to the manufacturing systems. Uncertain projections about future sales, fluctuations in quantities, new manufacturing technologies and shorter product life cycles with changing product requirements, at the same time with an increasing range of variants requires a continuous transformation of production structures to the current requirements on the market. As a consequence, methods for evaluating a company's production flexibility are of great significance. The following article discusses the experience gained in research results in medium-sized production. The use of the IT-framework “WertProNET” that emerged from these results shows the impact that production changes have on economical plant operation, and how unnecessary additional costs from the inefficient use of resources can be avoided.}, keywords = {change management, flexibility measurement, Genetic algorithm, manufacturing, resource efficiency}, pubstate = {published}, tppubtype = {inproceedings} } For years, production companies have faced an increasingly complex and rapidly changing market, which results in higher client customization. These coupled with a high complexity of cause-effect relationships of industries, globally-dispersed markets, technologies and economic areas create great challenges to the manufacturing systems. Uncertain projections about future sales, fluctuations in quantities, new manufacturing technologies and shorter product life cycles with changing product requirements, at the same time with an increasing range of variants requires a continuous transformation of production structures to the current requirements on the market. As a consequence, methods for evaluating a company's production flexibility are of great significance. The following article discusses the experience gained in research results in medium-sized production. The use of the IT-framework “WertProNET” that emerged from these results shows the impact that production changes have on economical plant operation, and how unnecessary additional costs from the inefficient use of resources can be avoided. |
2011 |
Rogalski, Sven; Wicaksono, Hendro Methodology for Flexibility Measurement in Semi-automatic Production Book Chapter ElMaraghy, Hoda A (Ed.): pp. 141-146, Springer Berlin Heidelberg, Berlin, Heidelberg, 2011, ISBN: 978-3-642-23860-4. Abstract | Links | BibTeX | Tags: flexibility measurement, manufacturing, resource efficient manufacturing @inbook{Rogalski2011, title = {Methodology for Flexibility Measurement in Semi-automatic Production}, author = {Sven Rogalski and Hendro Wicaksono}, editor = {Hoda A. ElMaraghy}, url = {https://link.springer.com/chapter/10.1007%2F978-3-642-23860-4_23}, doi = {10.1007/978-3-642-23860-4_23}, isbn = {978-3-642-23860-4}, year = {2011}, date = {2011-09-15}, pages = {141-146}, publisher = {Springer Berlin Heidelberg}, address = {Berlin, Heidelberg}, abstract = {Demands on production systems are changing constantly as a result of changing competitive conditions and are also closely linked to the performance goals of time, quality, costs and innovation ability. This results in an ever increasing selection between various competitors, with the most important selection criteria being customer individualization, an increasingly shorter product life cycle and new technological innovations. This situation creates an existential need for production companies to manage to adapt over time to the changed surrounding conditions and plan their resources in a way that makes them suitable for cost-effective and market-oriented manufacturing. The following article presents the computerized methodology of an innovative evaluation technique called ecoFLEX which allows the measurement of a production system's flexibility. At first the paper details the general concept for estimating production flexibility and the approach to concretely calculating the flexibility on different production levels. Furthermore, it presents the practical experience gained in ecoFLEX during its application at a small and medium enterprise (SME) to evaluate the complex manufacturing coherencies from the perspective of their efficiency. Especially it will be shown how the usage of flexibility indices calculated by ecoFLEX helps to come to the right decision on the strategic and operational level in production systems.}, keywords = {flexibility measurement, manufacturing, resource efficient manufacturing}, pubstate = {published}, tppubtype = {inbook} } Demands on production systems are changing constantly as a result of changing competitive conditions and are also closely linked to the performance goals of time, quality, costs and innovation ability. This results in an ever increasing selection between various competitors, with the most important selection criteria being customer individualization, an increasingly shorter product life cycle and new technological innovations. This situation creates an existential need for production companies to manage to adapt over time to the changed surrounding conditions and plan their resources in a way that makes them suitable for cost-effective and market-oriented manufacturing. The following article presents the computerized methodology of an innovative evaluation technique called ecoFLEX which allows the measurement of a production system's flexibility. At first the paper details the general concept for estimating production flexibility and the approach to concretely calculating the flexibility on different production levels. Furthermore, it presents the practical experience gained in ecoFLEX during its application at a small and medium enterprise (SME) to evaluate the complex manufacturing coherencies from the perspective of their efficiency. Especially it will be shown how the usage of flexibility indices calculated by ecoFLEX helps to come to the right decision on the strategic and operational level in production systems. |