Complexity management is one of the most crucial and challenging issues in manufacturing.As an emerging technology,digital twin provides an innovative approach to manage complexity in a more autonomous,analytical and ...Complexity management is one of the most crucial and challenging issues in manufacturing.As an emerging technology,digital twin provides an innovative approach to manage complexity in a more autonomous,analytical and comprehensive manner.This paper proposes an innovative framework of digital twin-driven complexity management in intelligent manufacturing.The framework will cover three sources of manufacturing complexity,including product design,production lines and supply chains.Digital twin provides three services to manage complexity:(1)real-time monitors and data collections;(2)identifications,diagnoses and predictions of manufacturing complexity;(3)fortification of human-machine interaction.A case study of airplane manufacturing is presented to illustrate the proposed framework.展开更多
Research on the sustainable development system (SDS) and its management by the theory and method of complexity science is very important to coordinate social economic and environmental development. This paper focuses ...Research on the sustainable development system (SDS) and its management by the theory and method of complexity science is very important to coordinate social economic and environmental development. This paper focuses on the features of the SDS, including irreversibility and nonlinearity, openness and strong coupling, dynamic and catastrophe, feedback and controllability. It also studies the complexity of sustainable development management and puts forward several questions needed for thorough study in future.展开更多
This paper presents a new optimisation approach for variance within a supply chain management process.The approach is presented by the variance cube of purchasing(VCP)that involves a lean method for variance optimisat...This paper presents a new optimisation approach for variance within a supply chain management process.The approach is presented by the variance cube of purchasing(VCP)that involves a lean method for variance optimisation,namely the cost and variance driver analysis.The approach focuses on the optimisation and the control of existing process variance within the supply chain.The application of the cube is presented by a case study involving a globally acting Tier 1 supplier,who produces steering systems for passenger cars and commercial vehicles.In this case,the sourcing process of this Tier 1 supplier will be analysed,evaluated and optimised regarding variance.The variance is presented in the form of the number of suppliers who are involved in the sourcing process.Unnecessary existing process variance,like an unnecessary huge number of suppliers within the sourcing process,is a type of waste.Time,money,quality and technology can be saved through a greater understanding of the optimal number of suppliers within a sourcing process.The results of the case study led to a generalised method to optimise the existing process variance,present cost improvements as well as optimising the key performance indicator to manage the number of suppliers in the sourcing process.The general approach can be used for other company departments like logistics and for different industries other than automotive.The insights of this article support the operative user and the strategic company management in order to reduce and improve unnecessary variance in different sections.The structured analysis of supply chain process variance via the VCP and the key performance indicator“optimal supplier number per sourcing process”are new to company management.展开更多
基金This research is funded by the Key Project of International(Regional)Cooperation and Exchange of the National Natural Science Foundation of China(52120105008).The principal investigators are Fei Tao and Ang Liu.
文摘Complexity management is one of the most crucial and challenging issues in manufacturing.As an emerging technology,digital twin provides an innovative approach to manage complexity in a more autonomous,analytical and comprehensive manner.This paper proposes an innovative framework of digital twin-driven complexity management in intelligent manufacturing.The framework will cover three sources of manufacturing complexity,including product design,production lines and supply chains.Digital twin provides three services to manage complexity:(1)real-time monitors and data collections;(2)identifications,diagnoses and predictions of manufacturing complexity;(3)fortification of human-machine interaction.A case study of airplane manufacturing is presented to illustrate the proposed framework.
基金This work is supported by National Natural Science Foundation of China ( No.70 0 71 0 4 1 )
文摘Research on the sustainable development system (SDS) and its management by the theory and method of complexity science is very important to coordinate social economic and environmental development. This paper focuses on the features of the SDS, including irreversibility and nonlinearity, openness and strong coupling, dynamic and catastrophe, feedback and controllability. It also studies the complexity of sustainable development management and puts forward several questions needed for thorough study in future.
文摘This paper presents a new optimisation approach for variance within a supply chain management process.The approach is presented by the variance cube of purchasing(VCP)that involves a lean method for variance optimisation,namely the cost and variance driver analysis.The approach focuses on the optimisation and the control of existing process variance within the supply chain.The application of the cube is presented by a case study involving a globally acting Tier 1 supplier,who produces steering systems for passenger cars and commercial vehicles.In this case,the sourcing process of this Tier 1 supplier will be analysed,evaluated and optimised regarding variance.The variance is presented in the form of the number of suppliers who are involved in the sourcing process.Unnecessary existing process variance,like an unnecessary huge number of suppliers within the sourcing process,is a type of waste.Time,money,quality and technology can be saved through a greater understanding of the optimal number of suppliers within a sourcing process.The results of the case study led to a generalised method to optimise the existing process variance,present cost improvements as well as optimising the key performance indicator to manage the number of suppliers in the sourcing process.The general approach can be used for other company departments like logistics and for different industries other than automotive.The insights of this article support the operative user and the strategic company management in order to reduce and improve unnecessary variance in different sections.The structured analysis of supply chain process variance via the VCP and the key performance indicator“optimal supplier number per sourcing process”are new to company management.