Next Article in Journal
Robust Control Design for Autonomous Vehicles Using Neural Network-Based Model-Matching Approach
Previous Article in Journal
Analysing the Performance of Ammonia Powertrains in the Marine Environment
Article

Analysis of Energy Efficient Scheduling of the Manufacturing Line with Finite Buffer Capacity and Machine Setup and Shutdown Times

Department of Engineering Processes Automation and Integrated Manufacturing Systems, Silesian University of Technology, Konarskiego 18A, 44-100 Gliwice, Poland
*
Author to whom correspondence should be addressed.
Academic Editors: Valentina Colla and Wen-Hsien Tsai
Energies 2021, 14(21), 7446; https://doi.org/10.3390/en14217446
Received: 8 August 2021 / Revised: 26 October 2021 / Accepted: 3 November 2021 / Published: 8 November 2021
(This article belongs to the Section C3: Energy and Climate Change)
The aim of this paper is to present a model of energy efficient scheduling for series production systems during operation, including setup and shutdown activities. The flow shop system together with setup, shutdown times and energy consumption are considered. Production tasks enter the system with exponentially distributed interarrival times and are carried out according to the times assumed as predefined. Tasks arriving from one waiting queue are handled in the order set by the Multi Objective Immune Algorithm. Tasks are stored in a finite-capacity buffer if machines are busy, or setup activities are being performed. Whenever a production system is idle, machines are stopped according to shutdown times in order to save energy. A machine requires setup time before executing the first batch of jobs after the idle time. Scientists agree that turning off an idle machine is a common measure that is appropriate for all types of workshops, but usually requires more steps, such as setup and shutdown. Literature analysis shows that there is a research gap regarding multi-objective algorithms, as minimizing energy consumption is not the only factor affecting the total manufacturing cost—there are other factors, such as late delivery cost or early delivery cost with additional storage cost, which make the optimization of the total cost of the production process more complicated. Another goal is to develop previous scheduling algorithms and research framework for energy efficient scheduling. The impact of the input data on the production system performance and energy consumption for series production is investigated in serial, parallel or serial–parallel flows. Parallel flow of upcoming tasks achieves minimum values of makespan criterion. Serial and serial–parallel flows of arriving tasks ensure minimum cost of energy consumption. Parallel flow of arriving tasks ensures minimum values of the costs of tardiness or premature execution. Parallel flow or serial–parallel flow of incoming tasks allows one to implement schedules with tasks that are not delayed. View Full-Text
Keywords: energy-efficient scheduling; flow shop; serial–parallel flow; multi objective immune algorithm energy-efficient scheduling; flow shop; serial–parallel flow; multi objective immune algorithm
Show Figures

Figure 1

MDPI and ACS Style

Kampa, A.; Paprocka, I. Analysis of Energy Efficient Scheduling of the Manufacturing Line with Finite Buffer Capacity and Machine Setup and Shutdown Times. Energies 2021, 14, 7446. https://doi.org/10.3390/en14217446

AMA Style

Kampa A, Paprocka I. Analysis of Energy Efficient Scheduling of the Manufacturing Line with Finite Buffer Capacity and Machine Setup and Shutdown Times. Energies. 2021; 14(21):7446. https://doi.org/10.3390/en14217446

Chicago/Turabian Style

Kampa, Adrian, and Iwona Paprocka. 2021. "Analysis of Energy Efficient Scheduling of the Manufacturing Line with Finite Buffer Capacity and Machine Setup and Shutdown Times" Energies 14, no. 21: 7446. https://doi.org/10.3390/en14217446

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop