System dynamics analysis of energy usage: case studies in automotive manufacturing

Abstract

Our life is strongly linked with the usage of natural resources. Energy is a necessity in everyday life and is often generated using non-renewable natural resources which are finite. Energy consumption in manufacturing industry is increasing and the way it is consumed is not sustainable. There is great concern about minimizing consumption of energy in manufacturing industry to sustain the natural carrying capacity of the ecosystem. This is one of the challenges in today's industrial world.In this paper two case studies have been carried out in crankshaft machining and cylinder head casting processes. The outcome of this research enables the company to identify potential avenues to optimize energy usage and offers a decision support tool.

Energy efficiency decision-making in non-energy intensive industries: content and social network analysis

“…The other studies address the theme of indicators and measurements of performance in energy efficiency as complementary elements for the development of models to assist in the evaluation and the decision-making using different approaches, such as linear programming (Karlsson, 2011), dynamics modeling systems (Adane et al, 2014), multicriteria decision (Boehner, 2015;Li et al, 2020), DEA (Kim et al, 2015;Simeonovski et al, 2021), computational simulation (Cassettari et al, 2017;Ionescu & Darie, 2020), mathematical model (Sarkar et al, 2019) and fuzzy logic (Dong & Huo, 2017;Çoban et al, 2020).…”

“…Despite being comprehensive, this approach presents a linear process, without considering the possible interrelationships between internal and external variables. Other studies have used techniques such as Monte Carlo (Cassettari et al, 2017;Knobloch & Mercure, 2016), simulation of discrete events (Cassettari et al, 2017;Sáenz et al, 2012;Horschig & Thrän, 2017), optimization (Karlsson, 2011;Sáenz et al, 2012;Hasan & Trianni, 2020;Sarkar et al, 2019;Ionescu & Darie, 2020;Simeonovski et al, 2021;Roemer & Strassburger, 2019) and system dynamic modeling (Adane et al, 2014;Zeng et al, 2015;Horschig & Thrän, 2017;Martins et al, 2020).…”

Towards a Generic Framework for the Performance Evaluation of Manufacturing Strategy: An Innovative Approach

“…To figure out the defined problem, the present methodology studies the system as a whole rather than using an analytical approach which breaks down the problem into smaller parts. Analyzing the structure of the system as a whole makes it possible to identify the non-linear causal relationships among the system parameters and to understand the structure of the complex system [35,39].…”

“…In complex environments, like a manufacturing system, objects often create feedback loops, where a change in one parameter affects the others dynamically, which feeds back to the original object, and so on. The interplay among objects determines the different states that the system can assume over the course of time, which is known as the dynamic behavior of the system [35]. The dynamic complexity of the system arises not from the number of system components, but from the combination of interactions among system elements over time [36,37].…”

The value of group model building: a stakeholder perspective

“…SD is a suitable modelling methodology when the analysed problem has wide temporal boundaries, focusing on the behaviour patterns that isolated events lead to (Forrester, 1961;Sterman, 2000). The method has been used in all kinds of projects, even large-scale collaborative modelling of critical infrastructure protection projects as Hernantes et al (2012) describe in a case study, to analyse energy usage for automotive manufacturing (Adane and Nicolescu, 2014) or to research quality in manufacturing (Gunasekaran et al, 2002), to name a few. Zwikael et al (2012) underscore the importance of collaboration, engagement with stakeholders and stakeholder management in virtual projects, but it is equally important for non-virtual projects and crucial for project success.…”