The Environmental Impact Assessment of a Company’s Manufacturing System

2015 ◽  
Author(s):  
Dimitrios Anagnostakis ◽  
James M. Ritchie ◽  
Theodore Lim ◽  
Conor Craig ◽  
Jamie Speedie
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Production System ◽  
Manufacturing System ◽  
Discrete Event ◽  
Event Simulation ◽  
System A ◽  
Ideal System ◽  
Save Energy ◽  
A Company

The major objective of this study is the estimation of the environmental impacts of a company’s manufacturing system. For this purpose, environmental key performance indicators are selected related to the energy consumption and pollutant gas emissions. To obtain accurate results and achieve an evaluation of the production system, a discrete event simulation tool was equipped. In this way, the production processes of a company were modelled and simulated in order to be assessed with regards to their environmental performance and impacts. The assessment of the investigated manufacturing system was carried out, by comparing it against a hypothetical ideal system of 100% efficiency in order for potential reductions in energy consumption and carbon emissions to be identified. Additionally, a supplementary use of the proposed methodology is presented showing that modelling the production system in advance a company can save energy and associated costs as well as reduce carbon emissions.

scholarly journals IMPROVABILITY OF THE FABRICATION LINE IN A SHIPYARD

Brodogradnja ◽  
2021 ◽  
Vol 72 (3) ◽  
pp. 13-28
Author(s):  
Neven Hadžić ◽  
◽  
Viktor Ložar ◽  
Tihomir Opetuk ◽  
Hrvoje Cajner
Keyword(s):  
Continuous Improvement ◽  
Production System ◽  
Manufacturing System ◽  
Discrete Event ◽  
Event Simulation ◽  
Work In Process ◽  
Bottleneck Identification ◽  
Potential Benefits ◽  
System Properties ◽  
The Mathematical Model

The ship production process is a complex manufacturing system involving numerous working stations mutually interconnected by transport devices and buffers. Such a production system can be efficiently modeled using the stochastic system approach and Markov chains. Once formulated, the mathematical model enables analysis of the governing production system properties like the production rate, work-in-process, and probabilities of machine blockage and starvation that govern the production system bottleneck identification and its continuous improvement. Although the continuous improvement of the production system is a well-known issue, it is usually based on managerial intuition or more complex discrete event simulation yielding sub-optimal results. Therefore, a semi-analytical procedure for the improvability analysis using the Markov chain framework is presented in this paper in the case of the shipyard’s fabrication lines. Potential benefits for the shipyards are pointed out as the main gain of the improvability analysis.

scholarly journals A Methodology to Adapt and Understand a Manufacturing System and Operations using Discrete-Event Simulatio

2019 ◽  
Vol 8 (6) ◽  
pp. 4998-5003
Keyword(s):  
Discrete Event Simulation ◽  
Manufacturing Industry ◽  
Manufacturing System ◽  
Discrete Event ◽  
The State ◽  
State Variables ◽  
Event Simulation ◽  
Potential Benefits ◽  
Short Hand

Discrete-Event Simulation (DES) is concerned with system and modeling of that system, where the state of the system is transformed at different discrete points from time to time, and several event occurs from time to time and the changes in state variables will transform then activities/attributes connected to these state variables changes according to the event. It is a robust methodology in the manufacturing industry for strategic, tactical, and operational applications for an organization, and yet organizations ignore to use simulation and do not rely on it. Moreover, companies that are using DES are not using the potential benefits but merely used as a short-hand basis for problems like bottlenecks, optimization, and in later stages of production like PLM, this paper aims to apply and analyze Discrete-Event Simulation through a Manufacturing System. The work describes here is to understand the concept of simulation for a system and to practice Discrete Event methodology

scholarly journals An Entropy-Based Formulation for the Support of Sustainable Mass Customization 4.0

2020 ◽  
Vol 2020 ◽  
pp. 1-21
Author(s):  
César Martínez-Olvera
Keyword(s):  
Energy Consumption ◽  
Mass Customization ◽  
Industry 4.0 ◽  
Manufacturing Industry ◽  
Discrete Event ◽  
Energy Productivity ◽  
Event Simulation ◽  
Managerial Implications ◽  
Optimal Resource ◽  
Information And Communication

Industry 4.0, an information and communication umbrella of terms that includes the Internet of Things (IoT) and cyber-physical systems, aims to ensure the future of the manufacturing industry competing in a proper environment of mass customization: demand for short delivery time, high quality, and small-lot products. Within this context of an Industry 4.0 mass customization environment, success depends on its sustainability, where the latter can only be achieved by the manufacturing efficiency of the smart factory-based Industry 4.0 transforming processes. Even though Industry 4.0 is associated with an optimal resource and energy productivity/efficiency, it becomes necessary to answer if the integration of Industry 4.0 elements (like CPS) has a favorable sustainability payoff. This requires performing energy consumption what-if analyses. The original contribution of this paper is the use of the entropy-based formulation as an alternative way of performing the initial steps of the energy consumption what-if analyses. The usefulness of the proposed approach is demonstrated by comparing the results of a discrete-event simulation model of mass customization 4.0 environment and the values obtained by using the entropy-based formulation. The obtained results suggest that the entropy-based formulation acts as a fairly good trend indicator of the system’s performance parameters increase/decrease. The managerial implications of these findings are presented at the end of this document.

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