Environmental Burden Analyzer for Machine Tool Operations and Its Application

Narita, Hirohisa

doi:10.5772/35991

Cited by 11 publications

(8 citation statements)

References 6 publications

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“…A relationship between production and GHG emissions released from production has been presented in Jaber et al (2013) that is based on Bogaschewsky (1995). Narita (2012) empirically verify a similar relationship for machine tools. As presented in Bazan et al (2015b) the annual cost of GHG emissions from production (manufacturing and remanufacturing) is written as:…”

Section: Cost Functionsmentioning

confidence: 76%

“…(5.7) Jaber et al (2013) show the relationship for GHG emissions based on Bogaschewsky (1995) that has also been verified empirically for machine tools in Narita (2012). A similar relationship can be used for the remanufacturing process and therefore the cost of GHG emissions can be given as:…”

mentioning

confidence: 86%

“…where a, b, and c can be empirically validated: Narita (2012) showed how to analyse the environmental burden of operating a machine tool and presented a relationship of equivalent CO2 emissions to be of the same form as that presented in Eq. (4.3) above; see Eq.…”

Section: Base-model I: Classical Coordinationmentioning

confidence: 99%

“…(4.3) above; see Eq. ( 10) on page 258 in Narita (2012). Narita's (2012) experiments showed that as the cutting speed is increased, the tool wear becomes significantly higher and thus the tool life is shortened, which increases the associated environmental burden (in terms of equivalent CO2 emissions).…”

Section: Base-model I: Classical Coordinationmentioning

confidence: 99%

“…( 10) on page 258 in Narita (2012). Narita's (2012) experiments showed that as the cutting speed is increased, the tool wear becomes significantly higher and thus the tool life is shortened, which increases the associated environmental burden (in terms of equivalent CO2 emissions). However, the environmental burden associated with the electrical consumption of the machine tool, the lubricant and cooling liquid is proportionate to time, which indicates that there is a trade-off relationship with respect to the cutting speed.…”

Section: Base-model I: Classical Coordinationmentioning

confidence: 99%

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Modeling environmentally responsible supply chains

Bazan¹

2021

Preprint

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Numerous literature reviews and research studies have highlighted the increasing environmental concerns of supply chain stakeholders (managers, legislative bodies, customers, etc.). Guaranteeing environmentally conscious supply chain operations is closely linked to an organization’s sustainability and success. A large part of this is the responsible management of product return flows in production and inventory environments. Reverse logistics is inevitable in today’s business environment with the most common reasons being product returns, incorrect product delivery, damaged products, and product exchange programs. Green concepts and should be operationalized in a supply chain context. The literature emphasizes that the modelling of reverse logistics and closed-loop supply chains from a green and/or environmental aspect lacks investigation and development. Mathematical modelling of such systems will assist decisionmaking processes and provided a better understanding of environmentally responsible inventory models. This thesis reviews the literature on the modelling of reverse logistics inventory systems that are based on the economic order/production quantity (EOQ/EPQ) and the joint economic lot size (JELS) settings so as to systematically analyse the mathematics involved in capturing the main characteristics of related processes. The literature is surveyed and classified according to the specific issues faced and modelling assumptions. Special attention is given to environmental issues. There are indications of the need for the mathematics of reverse logistics models to follow current trends in ‘greening’ inventory and supply-chain models. The modelling of waste disposal, greenhouse-gas emissions and energy consumption during production is considered as the most pressing priority for the future of inventory models. Mathematical models for two-level supply chains with different coordination policies, a manufacturing-remanufacturing inventory model and a two-level closed-loop supply chain model with remanufacturing under different coordination are developed in this thesis. Numerical examples are presented and discussed presenting managerial insights and implications. Input-Output system analysis and multi-objective optimization modeling are suggested future research directions.

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