A simulation-based methodology for the analysis of the effect of lean tools on energy efficiency: An application in power distribution industry

Baysan, Serdar; Kabadurmuş, Özgür; Çevikcan, Emre; Satoğlu, Şule Itır; Durmuşoğlu, Mehmet

doi:10.1016/j.jclepro.2018.11.217

Cited by 58 publications

(31 citation statements)

References 50 publications

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“…With a little innovative tinkering, several processes were implemented which provided solutions and produced more value in highly effective waysutilising less human effort, time and inventories, less energy, and fewer resources (Abreu, Alves &Moreira, 2017). However, current business challenges necessitate systems beyond efficient and responsive production processes, to include eco-efficient systems (see Cherrafi et al, 2018;Orji &Liu, 2018;Baysan et al, 2019) hence systems that create more value with lower environmental impacts (Dieste et al, 2019).Both concepts, however, focus on lessening wastage in all forms, including those hardest or invisible to deal with (Abreu et al, 2017). These goals must be attained without increasing the production costs, without any hidden short-or long-term external environmental costs, and to enhance long-term sustainability and firm survival (WBCSD, 2000).…”

Section: Lean Strategy and Firm Growthmentioning

confidence: 99%

“…Lean implementation enhances a firm's capability for eliminating wastage from business processes (Baysan et al, 2019). Conventionally, the lean literature focuses on the seven deadly dimensions of wastes: defects, overproduction, unnecessary motion, waiting, unnecessary inventory, transport, and inappropriate processing (Pojasek, 2008;Fercoq et al,2016;Dieste et al, 2019).…”

Section: Lean Strategy and Firm Growthmentioning

confidence: 99%

“…Table 1 reports a summary of the nexus between the deadly wastes (usually denoted as mudasin Japanese) and their potential green impacts (US EPA, 2007;Baysan et al, 2019). As an illustration, overproduction produces surplus products which may either spoil or go obsolete, and subsequently necessitate disposal.…”

Section: Lean Strategy and Firm Growthmentioning

confidence: 99%

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Going green, going clean: Lean‐green sustainability strategy and firm growth

et al. 2019

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Despite the widespread recognition of the paybacks of "going green" and "going clean", limited research has focused on the impact of lean-green strategy on firm growth. In this study, we contribute to strategy and environmental sustainability literatures by investigating the possibility that the influence on lean-green strategy and firm growth is driven by different levels of industry competition, managerial power and family ties. Using panel data from 732 firms in four major industrialised economies (the US, Germany, France and the UK), we found that lean-green strategy positively relates to firm growth and this relationship is amplified at higher levels of competition, managerial power and family ties. Theoretical and practical implications of the study are also discussed.

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Section: Lean Strategy and Firm Growthmentioning

confidence: 99%

Section: Lean Strategy and Firm Growthmentioning

confidence: 99%

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Going green, going clean: Lean‐green sustainability strategy and firm growth

et al. 2019

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“…In the context of increased demand for a higher degree of product customization and personalization, simulation leads to resource economy [28][29][30]. Manufacturing processes simulation, as an intermediate stage in implementing digital manufacturing asks for the use of specific technologies and methods [31][32][33][34][35][36][37][38][39].…”

Section: Production Process Simulationmentioning

confidence: 99%

Agent-Based Simulation of Value Flow in an Industrial Production Process

et al. 2019

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The current competitive environment demands companies to be more and more efficient. In order to increase manufacturing efficiency, two apparently independent approaches have emerged: lean strategies, focusing on identifying and minimizing non-added value activities, identifying wastes in the system and their elimination, and information tools for planning and controlling activities. In this paper, a manufacturing system was considered for which it was necessary to increase the production capacity in order to respond to the customer’s increased demand. A practical case study in the automotive industry for a medium-sized enterprise was considered. In order to investigate the production process parameters and to implement lean principles, Value Stream Mapping (current analysis and optimized solution) and Anylogic agent-based simulations were carried out. Based on this, the lean performances, specific for the target VSM, were evaluated in terms of key performance indicators. The benefits of integrating agent-based simulation in the design and analysis of the value flow in the production chain are the capitalization of the information offered by Value Stream Mapping and the possibility to choose the best one from the possible scenarios. It generates important time and cost reductions without further resource waste.

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“…In order to achieve such, it is vital to reduce bottlenecks and waste sources and aim to achieve maximum efficiency. Lean manufacturing is a revolutionary philosophy that identifies non-value-adding activities as waste and ultimately aims to eliminate such activities from all processes [1][2][3][4]. Many tools have been used to achieve lean manufacturing, such as cellular manufacturing, Just in Time (JIT), total productive maintenance (TPM), 5S and Value stream mapping (VSM).…”

Section: Introductionmentioning

confidence: 99%

Hybrid Integrations of Value Stream Mapping, Theory of Constraints and Simulation: Application to Wooden Furniture Industry

et al. 2019

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This paper studies manufacturing processes in a wooden furniture manufacturing company. The company suffers from long manufacturing lead times and an unbalanced production line. To identify sources of waste and delay value stream mapping (VSM) and a discrete event simulation model is implemented. VSM is used to visualize and analyze the major processes of the company and provide quantifiable KPIs; the manufacturing lead-time and then Overall Equipment Effectiveness (OEE) settings. A discrete event simulation model is then built to analyze the company on a wider scale and provide the data required to identify bottlenecks. Building on the data gathered from the production lines and the simulation model, two-bottleneck detection methods are used, the utilization method, and the waiting time method. Then based on the comparison of the two methods a third bottleneck detection is utilized; the scenario-based method, to identify the primary and secondary bottlenecks. After the bottlenecks are identified, changes are then evaluated using the simulation model and radar charts were built based on the improved simulation model, which evaluates the effect of changes in the utilization and OEE results. This work managed to neutralize the effect of one of the main bottlenecks and minimize the effect of the other. The manufacturing utilization was increased by 15.8% for the main bottleneck resources followed by 2.4% for the second one. However, it is hard to convince the traditional administration of this small size manufacturing plant to adopt a completely revolutionizing, costly, and risky (at such level) lean manufacturing approach. This paper studies and provides a much lower in cost and verified scheme of enhancement.

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A simulation-based methodology for the analysis of the effect of lean tools on energy efficiency: An application in power distribution industry

Cited by 58 publications

References 50 publications

Going green, going clean: Lean‐green sustainability strategy and firm growth

Going green, going clean: Lean‐green sustainability strategy and firm growth

Agent-Based Simulation of Value Flow in an Industrial Production Process

Hybrid Integrations of Value Stream Mapping, Theory of Constraints and Simulation: Application to Wooden Furniture Industry

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