Environmental aspects in manufacturing system modelling and simulation—State of the art and research perspectives

Thiede, Sebastian; Seow, Yingying; Andersson, Jon; Johansson, Björn

doi:10.1016/j.cirpj.2012.10.004

Cited by 97 publications

(58 citation statements)

References 14 publications

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“…Thiede et al argue that environmentally related aspects are currently not sufficiently considered as standard functions in manufacturing system simulation tools [31]. One potential solution approach is presented by Herrmann et al where a flexible energy flow-oriented manufacturing system was simulated [32].…”

Section: Sustainable Energymentioning

confidence: 99%

More Sustainability in Industry through Industrial Internet of Things?

2018

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Industrial production plays an important role for achieving a green economy and the sustainable development goals. Therefore, the nascent transformation of industrial production due to digitalization into a so-called Industrial Internet of Things (IIoT) is of great interest from a sustainable development point of view. This paper discusses how the environmental dimension of a sustainable development can potentially benefit from the IIoT-focusing especially on three topics: resource efficiency, sustainable energy and transparency. It presents a state of the art literature analysis of IIoT-enabled approaches addressing the three environmental topics. This analysis is compared with the findings of a survey among Chinese industrial companies, investigating the sustainability-related expectations of participants coming along with the implementation of IIoT solutions. China has been chosen as a case study because it brings together a strong industrial sector, ambitious plans regarding industrial digitalization and a high relevance and need for more sustainability. The survey was conducted with the means of a questionnaire which was distributed via email and used for direct on-site interviews. It focused on large and medium sized companies mainly from Liaoning Province and had a sample size of 109 participants.

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Section: Sustainable Energymentioning

confidence: 99%

More Sustainability in Industry through Industrial Internet of Things?

2018

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“…On the one hand, generic models are missing because grinding tools are often highly specialized. On the other hand, commercial tools to model manufacturing systems do not include environmental aspects sufficiently [54]. Energy and material costs are often substantial parts of the price and are therefore confidential.…”

Section: Discussionmentioning

confidence: 99%

Sustainability concerns in the life cycle of bonded grinding tools

Linke

2014

CIRP Journal of Manufacturing Science and Technology

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Manufacturing technologies need to become more sustainable, as do the tools used. Grinding is one of the most important finishing processes and grinding tools are complex products with a large variety of grit types, bond materials, and manufacturing routes. This study discusses the tool life stages from raw material production and tool manufacturing to tool use and end of life. The most important economic, environmental and social concerns are pointed out. This study highlights where more research and transparency in the supply chain is needed to achieve more sustainable grinding tools. Highlights:• Sustainability in grinding technology needs to include comprehensive studies on the life cycle of grinding tools.• This paper addresses the most important economic, environmental and social issues throughout all life stages of a grinding tool and therefore sets the stage for future quantitative evaluations.• This study highlights where more research and transparency in the supply chain is needed to achieve more sustainable grinding tools.

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“…Unsurprisingly, research into unit-process and process chain level energy simulation has increased in the past decade M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT (Heilala et al 2013;Thiede et al 2013;Wright et al 2013). Recent research by Thiede (2012a) aimed at a holistic energy simulation which considered all three levels of energy usage within a facility including all relevant energy flows (such as steam, compressed air and electricity).…”

Section: Energy Simulationmentioning

confidence: 99%

A simple energy usage toolkit from manufacturing simulation data

Wilson

Arokiam

Belaidi

et al. 2016

Journal of Cleaner Production

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A fundamental problem in the management of energy usage is the inability to clearly predict any possible energy saving opportunities. The cost of both under or overestimating potential returns on investment can be prohibitive to a decision maker. In recent years the simulation of energy usage using existing manufacturing simulation tools has increased in popularity among researchers, but it is decision makers who need to see the benefits of this discipline. This paper proposes an interactive manufacturing energy management toolkit which makes use of existing productivity simulation models for the prediction of energy usage. An interactive Microsoft ® Excel ® based toolkit is developed to control Lanner's WITNESS ® discrete-event simulation software using Microsoft ® Visual Basic ® for Applications. The toolkit has the ability to predict potential areas where energy saving opportunities can be made within a complex manufacturing line, and is accessible from management presentations and proposals. The interactivity of the toolkit provides an environment which facilitates efficient hypothesis testing. The paper includes an industrial case study where the approach was used to quantify theoretical savings from certain energy usage reduction scenarios within a complex automotive engine manufacturing line.

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Environmental aspects in manufacturing system modelling and simulation—State of the art and research perspectives

Cited by 97 publications

References 14 publications

More Sustainability in Industry through Industrial Internet of Things?

More Sustainability in Industry through Industrial Internet of Things?

Sustainability concerns in the life cycle of bonded grinding tools

A simple energy usage toolkit from manufacturing simulation data

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