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 |
Wicaksono Hendro; Ni, Tianran An Automated Information System for Medium to Short-Term Manpower Capacity Planning in Make-To-Order Manufacturing Journal Article Procedia Manufacturing, 52 , pp. 319-324, 2020. Abstract | Links | BibTeX | Tags: information systems, Information visualisation, production planning and control, resource efficient manufacturing @article{Wicaksono2020d, title = {An Automated Information System for Medium to Short-Term Manpower Capacity Planning in Make-To-Order Manufacturing}, author = {Wicaksono, Hendro; Ni, Tianran}, url = {https://doi.org/10.1016/j.promfg.2020.11.053}, doi = {10.1016/j.promfg.2020.11.053}, year = {2020}, date = {2020-12-31}, journal = {Procedia Manufacturing}, volume = {52}, pages = {319-324}, abstract = {In today’s tough economy, it is important for (Make-To-Order) MTO companies to be responsive to customer demand and market fluctuations and to keep the costs as low as possible at the same time. Unlike in Make-To-Stock (MTS), MTO companies hold capacity in reserve. Thus, they are able to make efficient utilization of available capacity to satisfy customer needs. This then leads to a constant capacity planning problem. The companies are facing fluctuations between overload by lack of sufficient capacity, and idleness by excess of capacity comparing to the level of demand. Among all the planning resources, the available manpower is one of the most essential parts of the MTO operations. Therefore, the allocation and adjustment of manpower capacity that suits different planning horizons is a predominant measure to meet the changing capacity demands. Nonetheless, a signing each individual labor to various types of tasks and orders on a day to day basis continually for the planning horizon of several weeks or months is difficult. This paper presents an approach of automated manpower planning model which can be used by MTO operations to achieve a better transparency and synchronization of capacity load for short to medium planning horizons. The approach is implemented as a software tool to automate the data processing and analysis, which helps to dramatically reduce the corresponding data operation efforts and planning time. This paper also presents the validation of the approach and tool in a real production unit in a German small MTO manufacturing company.}, keywords = {information systems, Information visualisation, production planning and control, resource efficient manufacturing}, pubstate = {published}, tppubtype = {article} } In today’s tough economy, it is important for (Make-To-Order) MTO companies to be responsive to customer demand and market fluctuations and to keep the costs as low as possible at the same time. Unlike in Make-To-Stock (MTS), MTO companies hold capacity in reserve. Thus, they are able to make efficient utilization of available capacity to satisfy customer needs. This then leads to a constant capacity planning problem. The companies are facing fluctuations between overload by lack of sufficient capacity, and idleness by excess of capacity comparing to the level of demand. Among all the planning resources, the available manpower is one of the most essential parts of the MTO operations. Therefore, the allocation and adjustment of manpower capacity that suits different planning horizons is a predominant measure to meet the changing capacity demands. Nonetheless, a signing each individual labor to various types of tasks and orders on a day to day basis continually for the planning horizon of several weeks or months is difficult. This paper presents an approach of automated manpower planning model which can be used by MTO operations to achieve a better transparency and synchronization of capacity load for short to medium planning horizons. The approach is implemented as a software tool to automate the data processing and analysis, which helps to dramatically reduce the corresponding data operation efforts and planning time. This paper also presents the validation of the approach and tool in a real production unit in a German small MTO manufacturing company. |
2013 |
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. |
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 |
Aleksandrov, Kiril; Wicaksono, Hendro; Rogalski, Sven Evaluation of Resource Flexibility in Digital Factory Planning in Small and Medium sized Enterprises Inproceedings FAIM, International Conference on Flexible Automation and Intelligent Manufacturing, pp. 61-70, Curran Associates, Red Hook, 2012, ISBN: 978-952-15-2783-8. Links | BibTeX | Tags: change management, digital factory, layout planning, production planning and control, SME oriented technology @inproceedings{Aleksandrov2012, title = {Evaluation of Resource Flexibility in Digital Factory Planning in Small and Medium sized Enterprises}, author = {Kiril Aleksandrov and Hendro Wicaksono and Sven Rogalski}, url = {https://www.tib.eu/en/search/id/tema%3ATEMA20140307649/Evaluation-of-Resource-Flexibility-in-Digital-Factory/}, isbn = { 978-952-15-2783-8}, year = {2012}, date = {2012-06-13}, booktitle = {FAIM, International Conference on Flexible Automation and Intelligent Manufacturing}, pages = {61-70}, publisher = {Curran Associates}, address = { Red Hook}, keywords = {change management, digital factory, layout planning, production planning and control, SME oriented technology}, pubstate = {published}, tppubtype = {inproceedings} } |