Joint Production and Energy Modeling of Sustainable Manufacturing Systems: Challenges and Methods

Author(s):  
Yong Wang ◽  
Lin Li

This paper proposes a framework for addressing challenges of joint production and energy modeling of sustainable manufacturing systems. The knowledge generated is used to improve the technological readiness of manufacturing enterprises for the transition towards sustainable manufacturing. Detailed research tasks of the framework are on the modeling of production, energy efficiency, electricity demand, cost, and demand response decision making. Specifically, the dynamics and performance measures of general manufacturing systems with multiple machines and buffers are modeled to integrate energy use into system modeling. The expressions of electrical energy efficiency and cost are then established based on the electricity pricing profile. Finally, joint production and energy scheduling problem formulations and the solution technique are discussed. New insights are acquired based on the applications of the established model in system parameter selection, rate plan switching decision making, and demand response scheduling. Appropriate implementation of this research outcome may lead to energy-efficient, demand-responsive, and cost-effective operations and thus improve the sustainability of modern manufacturing systems.

Author(s):  
Karl R. Haapala ◽  
Fu Zhao ◽  
Jaime Camelio ◽  
John W. Sutherland ◽  
Steven J. Skerlos ◽  
...  

Sustainable manufacturing requires simultaneous consideration of economic, environmental, and social implications associated with the production and delivery of goods. Fundamentally, sustainable manufacturing relies on descriptive metrics, advanced decision-making, and public policy for implementation, evaluation, and feedback. In this paper, recent research into concepts, methods, and tools for sustainable manufacturing is explored. At the manufacturing process level, engineering research has addressed issues related to planning, development, analysis, and improvement of processes. At a manufacturing systems level, engineering research has addressed challenges relating to facility operation, production planning and scheduling, and supply chain design. Though economically vital, manufacturing processes and systems have retained the negative image of being inefficient, polluting, and dangerous. Industrial and academic researchers are re-imagining manufacturing as a source of innovation to meet society's future needs by undertaking strategic activities focused on sustainable processes and systems. Despite recent developments in decision making and process- and systems-level research, many challenges and opportunities remain. Several of these challenges relevant to manufacturing process and system research, development, implementation, and education are highlighted.


Author(s):  
Xufeng Yao ◽  
Zeyi Sun ◽  
Lin Li ◽  
Hua Shao

The expenses associated with maintenance activities and energy consumption account for a large portion of the total operation cost in manufacturing plants. Therefore, effective methods that can be used for smart maintenance decision-making and energy management to reduce the costs of these two sections and improve the competitiveness of manufacturing enterprise are of high interests to industry. Many efforts focusing on maintenance decision-making and energy management have been dedicated. However, most of the existing research focusing on these two topics has been conducted separately, very little work has been done from a joint perspective that considers the benefits from both manufacturing machine reliability improvement and energy cost reduction. In this paper, a joint maintenance and energy management method is proposed to identify the maintenance actions considering energy cost as well as other equipment health metrics. A numerical case based on a section of an automotive assembly line is used to illustrate the potential benefits of the proposed approach.


Author(s):  
Leah Cuyler ◽  
Zeyi Sun ◽  
Lin Li

Electricity demand response is considered a promising tool to balance the electricity demand and supply during peak periods. It can effectively reduce the cost of building and operating those peaking power generators that are only run a few hundred hours per year to satisfy the peak demand. The research on the electricity demand response implementation for residential and commercial building sectors has been very mature. Recently, it has also been extended to the manufacturing sector. In this paper, a simulation-based optimization method is developed to identify the optimal demand response decisions for the typical manufacturing systems with multiple machines and buffers. Different objectives, i.e. minimizing the power consumption under the constraint of system throughput, and maximize the overall earnings considering the tradeoff between power demand reduction and potential production loss, are considered. Different energy control decisions are analyzed and compared regarding the potential influence on the throughput of manufacturing system due to the different control actions adopted by throughput bottleneck machine.


Author(s):  
Zeyi Sun ◽  
Stephan Biller ◽  
Fangming Gu ◽  
Lin Li

Due to rapid consumption of world’s fossil fuel resources and impracticality of large-scale application and production of renewable energy, the significance of energy efficiency improvement of current available energy modes has been widely realized by both industry and academia. A great deal of research has been implemented to identify, model, estimate, and optimize energy efficiency of single-machine manufacturing system [1–5], but very little work has been done towards achieving the optimal energy efficiency for a typical manufacturing system with multiple machines. In this paper, we analyze the opportunity of energy saving on the system level and propose a new approach to improve energy efficiency for sustainable production systems considering the fact that more and more modern machines have multiple power states. Numerical case based on simulation model of an automotive assembly line is used to illustrate the effectiveness of the proposed approach.


2020 ◽  
Vol 12 (17) ◽  
pp. 7006
Author(s):  
Josefine Rasmussen

Energy efficiency is an important means for sustainable manufacturing. One action for manufacturing companies to improve energy efficiency is through investments. While these investments often are profitable, opportunities remain unexploited. This paper explores the structural context of the investment decision-making process by examining the associated activities, procedures, and the role of information. While the structural context may limit complex investments that do not fit predefined rules and controls, such as energy efficiency and other sustainability-related investments, it remains a scarcely studied aspect of investment decision-making for energy efficiency investments. Method-wise, the paper is based on a case study of a major investment at a pulp and paper company, motivated and justified based on productivity, strategic, energy, and sustainability rationales. The paper contributes with illustrating how configurations of internal investment activities and procedures may be crucial for sustainability-related investments to pass through the investment process. Moreover, the configuration of activities and procedures is also indicated as influential for the way in which an investment is executed. Hence, for energy efficiency and other sustainability-related investments to make business sense constitutes more than achieving desirable payback periods; the structural context should be considered.


Author(s):  
Yang Li ◽  
Jun-Qiang Wang ◽  
Qing Chang

There has been an increasing trend for manufacturers to shift toward sustainable manufacturing strategies in response to an ever-growing pressure from fluctuating energy price and environmental crisis. Reducing energy consumption is considered as an important step to achieve the sustainability of a production system. This paper proposes an event-based control methodology to improve the production energy efficiency through strategically switching appropriate stations to energy saving mode. Based on an event-based analysis of production dynamics, an analytical approach is developed to quantitatively predict the system level production loss resulted from an energy saving control event (ESCE). A genetic-based control algorithm is proposed to balance the trade-off between the gain from energy saving and the expense of throughput loss. The energy improvement analysis results in a fundamental understanding of production energy dynamics and a significant decrease of energy cost for a manufacturing facility. Numerical case studies are performed to validate the effectiveness of the proposed method. It is found that the control method can effectively reduce energy cost, while only slightly impacting production.


Author(s):  
Xue Zhou ◽  
Jing Zhao ◽  
Lingxiang Yun ◽  
Zeyi Sun ◽  
Lin Li

Abstract Due to the rapidly rising energy price and increase in public awareness of environmental protection, the manufacturers are facing the ever-increasing moral and economic pressures from the community, government, and society. Hence, the significance of energy related studies in manufacturing systems has gradually become recognized in recent years. In most cases, the techniques to reduce the energy consumption are either renewable energy methods (solar, tidy and wind) or improving energy efficiency for existing energy modes. The approach to cut the energy related costs for manufacturing plants has not been comprehensively considered, although the same methods such as demand response and load shedding have been widely studied in the building research. In this paper, a brief analysis of the unique challenges to the application of the demand response technique in manufacturing systems is presented. The feasibility and profitability of demand response in manufacturing systems under the constraint of system throughput are studied and explored. An initial study about customer side decision making on demand response is introduced, and a numerical case of a section of a manufacturing system is used to show the benefits of the proposed idea, which illustrates over 6% bill reduction and over 5% consumption reduction during a billing cycle without sacrificing system throughput.


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