A kind of lean approach for removing wastes from non-manufacturing process with various facilities

Guang-yu, Xiong; Shang, Xiuqin; Xiong, Gang; Nyberg, Timo R.

doi:10.1109/jas.2019.1911351

Cited by 7 publications

(4 citation statements)

References 19 publications

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“…Consequently, a series of adjustments are needed in terms of people's behavior accordingly [6,47]. Meanwhile, the process change also brings about an organizational change [48], such as new roles, new mechanisms and new functions being established. The role of prosumers also brings about a new force to manufacturing resources for value-value capacity; a crowdsourcing mechanism can be applied to connect prosumers with upstream suppliers or manufacturers in the VC [4,8,47,49].…”

Section: Evolution Of Socialmmentioning

confidence: 99%

A Case Study in Social Manufacturing: From Social Manufacturing to Social Value Chain

Guang-yu

Helo

Ekstrom³

et al. 2022

Machines

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A new manufacturing mode, called social manufacturing, has been developing widely, and employed in many enterprises across the business value chain in recent years. Faced with this increasing dynamic, both enterprises and customers have to be more aware of the potential opportunity and benefit to be derived from this new manufacturing mode. One benefit is more value-adding potential for both enterprises upstream and customers downstream across the business value chain, compared with the normal mode. This research extends the application of social manufacturing to the entire business value chain system to bring new opportunities and value-adding potential for enterprises. This paper proposes a social value chain system that applies the social manufacturing mode to the entire value chain and contributes to three areas: (1) a new way of thinking for enterprises to create new opportunities to add value throughout the value chain by employing the social manufacturing mode; (2) establishing the social value chain system for all participants/enterprises across the chain in order to gain a win–win situation for all participants; and (3) suggesting some idea of a suitable performance measurement to monitor and evaluate the proposed social value chain system.

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Section: Evolution Of Socialmmentioning

confidence: 99%

A Case Study in Social Manufacturing: From Social Manufacturing to Social Value Chain

Guang-yu

Helo

Ekstrom³

et al. 2022

Machines

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“…Hamalainen et al [8] proposed the value chain design and analysis of SM Ecosystem. Shang et al [4], [5] and Xiong [6] constructed the footwear and apparel SM systems. With the development of intelligent manufacturing, 5G Network, and personalized product consumption, SM mode is developed quickly.…”

Section: Social Manufacturingmentioning

confidence: 99%

Social Manufacturing: A Paradigm Shift for Smart Prosumers in the Era of Societies 5.0

Wang

Shang

Qin

et al. 2019

IEEE Trans. Comput. Soc. Syst.

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“…Over the past decade, LMS was attaining a rising consideration as it serves as one of the method for productivity improvement and cost minimization in manufacturing (Xiong, et al, 2019;Möldner, et al, 2020). LMS mainly focuses on eliminating the wastes in the production process as initiated by Henry Ford.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Prediction Model: Optimized Neural Network for Lean Manufacturing Technology

Jobin

2021

JER is an international, peer-reviewed journal that publishes f

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Lean manufacturing (LM) is a method, which focuses on reducing wastes and increasing the productivity within manufacturing firms. Several analyses were performed on LM technology depending on minimal lead times, enhanced quality and reduced operating costs. However, limitation exists in understanding its role to develop managing commitment, worker involvement and in turn its organizational performance. This paper intends to propose a new Neural Network (NN) based intelligent prediction framework. The initial process is manual labeling or response validation, which is carried out by utilizing the responses attained for each questions under each factors including lean awareness, employee involvement, management commitment, lean technology, Organizational Performance (OP) and Organizational Support (OS). Subsequently, NN is exploited for prediction process, where the features (received responses) are given as input and the labeling values attained are set as target. Further, in order to improve the prediction performance, the NN training is performed by a new Hybrid Particle Swarm and Pigeon Optimization (HPS-PO) algorithm via tuning the optimal weights. In fact, the proposed algorithm is the combination of Particle Swarm Optimization (PSO) and Pigeon Optimization Algorithm (POA), respectively. Finally, the performance of the proposed model is examined over conventional methods in terms of prediction analysis and error analysis.

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A kind of lean approach for removing wastes from non-manufacturing process with various facilities

Cited by 7 publications

References 19 publications

A Case Study in Social Manufacturing: From Social Manufacturing to Social Value Chain

A Case Study in Social Manufacturing: From Social Manufacturing to Social Value Chain

Social Manufacturing: A Paradigm Shift for Smart Prosumers in the Era of Societies 5.0

Intelligent Prediction Model: Optimized Neural Network for Lean Manufacturing Technology

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