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Production engineering

About: Production engineering is a research topic. Over the lifetime, 2657 publications have been published within this topic receiving 37409 citations.


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Journal Article
TL;DR: In this paper, the authors carried out a research on the domestic development and trend of surface engineering in the recent five years, focusing on the engineering need of machine manufacture and the innovation and application of surface Engineering, mainly comments the new progress,achievement,view,methods and techniques of surface engineers in the fields of green manufacturing,energy saving and consumption reducing,maintenance and remanufacturing,new energy,biomedical science,light metal components,extreme environment and so on.
Abstract: In recent years,surface engineering developed from single surface engineering to multi–surface engineering,nanosurface engineering and their automation.The application of surface engineering ranges from resisting wear and corrosion to preventing fatigue and creep.The new growth of surface engineering rises in the frontier of information technology,biological technology and nano science and technology.Surface engineering gets a quick development in the aviation,aerospace,new energy,new material,environmental protection and resources circulation industries.This paper carried on a research on the domestic development and trend of surface engineering in the recent five years.Focusing on the engineering need of machine manufacture and the innovation and application of surface engineering,it mainly comments the new progress,achievement,view,methods and techniques of surface engineering in the fields of green manufacturing,energy saving and consumption reducing,maintenance and remanufacturing,new energy,biomedical science,light metal components,extreme environment and so on.

6 citations

Proceedings ArticleDOI
Matteo Confalonieri1, Andrea Barni1, Anna Valente1, Marco Cinus1, Paolo Pedrazzoli1 
22 Jun 2015
TL;DR: A Decision Support System enabling the early identification of problems occurring on manufacturing lines thus suggesting related recovery actions, together with the potential repercussions of their adoption, at economic and environmental level is described.
Abstract: Besides pursuing the economic goals of low costs and high profits, companies are becoming more and more aware of the environmental and social impact of their actions. Companies striving for the integrated optimization of environmental and economic perspectives within their production processes, need to be supported by tools helping to understand the effects of the decision making process. In this context, this paper describes a Decision Support System (DSS) enabling the early identification of problems occurring on manufacturing lines thus suggesting related recovery actions, together with the potential repercussions of their adoption, at economic and environmental level. The decision making process beneath the DSS starts from the aggregation of production lines sensors data in Key Performance Indicators (KPI). The data are then processed by means of an Artificial Neural Networks (ANN) based knowledge system which enables to suggest preventive maintenance interventions. The proposed maintenance activities, elaborated throughout a scheduling engine, are integrated within the weekly production schedule, according to the selected optimization policy. Preliminary tests have been carried out in manufacturing plants of IKEA industries and Brembo.

6 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20234
202210
202126
202025
201923
201857