Joint Maintenance and Energy Management of Sustainable Manufacturing Systems

2015 ◽  
Author(s):  
Xufeng Yao ◽  
Zeyi Sun ◽  
Lin Li ◽  
Hua Shao
Keyword(s):  
Decision Making ◽  
Energy Management ◽  
Energy Cost ◽  
Manufacturing Systems ◽  
Sustainable Manufacturing ◽  
Manufacturing Plants ◽  
Machine Reliability ◽  
Automotive Assembly ◽  
Maintenance Decision ◽  
Joint Maintenance

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.

Joint Maintenance and Energy Management in Manufacturing Systems: Prospect Discussion, Challenge Analysis, and a Case Study

2016 ◽  
Author(s):  
Xufeng Yao ◽  
Zeyi Sun ◽  
Dong Wei ◽  
Lingyun Wang
Keyword(s):  
Energy Management ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Energy Control ◽  
Research Directions ◽  
Equipment Reliability ◽  
Automotive Assembly ◽  
Potential Benefits ◽  
Joint Maintenance

The maintenance in manufacturing systems has been widely studied to improve equipment reliability, increase the productivity, and reduce operational cost. Recently, with the increasing concerns on climate change and environmental protection, the energy related performance of manufacturing system has also draw wide attention from both academia and industry. One common decision of maintenance and energy management can be the identification of the machines that could be shut down in the manufacturing system for either maintenance or energy saving purpose. Thus, the idea of implementing maintenance and energy control simultaneously has emerged. Some existing cases about the joint maintenance and energy control in manufacturing systems can be found in literature. In this paper, we further analyze the existing opportunities for joint energy and maintenance decision making in manufacturing systems. A few research directions towards this goal are proposed and discussed. The corresponding research challenges are also analyzed. A numerical case based on a section of an automotive assembly line is used to illustrate the potential benefits of the proposed approach.

scholarly journals A Review of Engineering Research in Sustainable Manufacturing

2013 ◽  
Vol 135 (4) ◽  
Author(s):  
Karl R. Haapala ◽  
Fu Zhao ◽  
Jaime Camelio ◽  
John W. Sutherland ◽  
Steven J. Skerlos ◽  
...  
Keyword(s):  
Decision Making ◽  
Manufacturing Process ◽  
Manufacturing Systems ◽  
Sustainable Manufacturing ◽  
Supply Chain Design ◽  
Planning And Scheduling ◽  
Engineering Research ◽  
Challenges And Opportunities ◽  
Recent Developments ◽  
Planning Development

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.

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

2014 ◽  
Author(s):  
Yong Wang ◽  
Lin Li
Keyword(s):  
Decision Making ◽  
Energy Efficiency ◽  
Demand Response ◽  
Manufacturing Systems ◽  
Energy Use ◽  
System Modeling ◽  
Sustainable Manufacturing ◽  
Energy Modeling ◽  
Joint Production ◽  
Solution Technique

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.

Event-Based Production Control for Energy Efficiency Improvement in Sustainable Multistage Manufacturing Systems

2018 ◽  
Vol 141 (2) ◽  
Author(s):  
Yang Li ◽  
Jun-Qiang Wang ◽  
Qing Chang
Keyword(s):  
Energy Efficiency ◽  
Energy Saving ◽  
Energy Cost ◽  
Manufacturing Systems ◽  
Production Control ◽  
Control Method ◽  
Sustainable Manufacturing ◽  
Environmental Crisis ◽  
System Level ◽  
Event Based

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.

Demand Response for Sustainable Manufacturing Systems Considering Buffer Content Utilization

2020 ◽  
Author(s):  
Xue Zhou ◽  
Jing Zhao ◽  
Lingxiang Yun ◽  
Zeyi Sun ◽  
Lin Li
Keyword(s):  
Demand Response ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Public Awareness ◽  
Sustainable Manufacturing ◽  
Initial Study ◽  
Load Shedding ◽  
System Throughput ◽  
Manufacturing Plants ◽  
Consumption Reduction

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.

Clean Manufacturing from Cradle to Cradle

2012 ◽  
Vol 502 ◽  
pp. 43-48
Author(s):  
M.E. Peralta ◽  
Francisco Aguayo González ◽  
Juan Ramón Lama Ruiz
Keyword(s):  
Manufacturing Systems ◽  
Sustainable Manufacturing ◽  
New Paradigm ◽  
Manufacturing Plants ◽  
Industrial Plants ◽  
Industrial Parks ◽  
Industrial Planning ◽  
Clean Manufacturing ◽  
Cradle To Cradle

The sustainability of manufacturing processes lies in industrial planning and productive activity. Industrial plants are characterized by the management of resource (inputs and outputs), processing and conversion processes, which usually are organized in a linear system. Good planning will optimize the manufacturing and promoting the quality of the industrial system. Cradle to Cradle is a new paradigm for engineering and sustainable manufacturing that integrates projects (industrial parks, manufacturing plants, systems and products) in a framework consistent with the environment, adapted to the society and technology and economically viable. To carry it out, we implement this paradigm in the MGE2 (Genomic Model of Eco-innovation and Eco-design), as a methodology for designing and developing products and manufacturing systems with an approach from the cradle to cradle.

Sustainable Manufacturing Oriented Prognosis for Facility Reuse

2010 ◽  
Vol 450 ◽  
pp. 437-440 ◽  
Author(s):  
Ji Hong Yan ◽  
Ding Guo Hua ◽  
Xing Wang
Keyword(s):  
Neural Networks ◽  
Decision Making ◽  
Sustainable Manufacturing ◽  
Time To Failure ◽  
Remaining Life ◽  
Failure Data ◽  
On Line ◽  
Reliability Methods ◽  
Maintenance Decision ◽  
Effective Condition

Reuse is considered as one of the most reasonable strategies to realize sustainability. This paper presents an efficient methodology of ann-based prognosis combined with reliability methods to evaluate and guarantee the reusability of facility. The methodology provides the prediction of the remaining life of facility utilizing artificial neural networks. Corresponding reliability is calculated through fitting Weibull distribution to in-house time-to-failure data. Maintenance decision is made by predicting the time when the reliability or remaining life of facility reach the thresholds decided by facility’s reusability. Application results show that the proposed methodology provides effective condition information for reuse decision making from both historical and on-line perspectives.

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