Energy Consumption Reduction for Sustainable Manufacturing Systems Considering Machines With Multiple-Power States

2011 ◽  
Author(s):  
Zeyi Sun ◽  
Stephan Biller ◽  
Fangming Gu ◽  
Lin Li
Keyword(s):  
Energy Efficiency ◽  
Manufacturing Systems ◽  
Large Scale ◽  
Manufacturing System ◽  
Production Systems ◽  
Sustainable Manufacturing ◽  
System Level ◽  
Model Estimate ◽  
Improve Energy Efficiency ◽  
Multiple Power

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.

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.

scholarly journals A review of energy-efficient scheduling in intelligent production systems

2019 ◽  
Vol 6 (2) ◽  
pp. 237-249 ◽  
Author(s):  
Kaizhou Gao ◽  
Yun Huang ◽  
Ali Sadollah ◽  
Ling Wang
Keyword(s):  
Energy Efficiency ◽  
Production Scheduling ◽  
Energy Cost ◽  
Energy Efficient ◽  
Manufacturing Systems ◽  
Production Systems ◽  
Future Research ◽  
Scheduling Problems ◽  
Improve Energy Efficiency ◽  
Energy Efficient Scheduling

Abstract Recently, many manufacturing enterprises pay closer attention to energy efficiency due to increasing energy cost and environmental awareness. Energy-efficient scheduling of production systems is an effective way to improve energy efficiency and to reduce energy cost. During the past 10 years, a large amount of literature has been published about energy-efficient scheduling, in which more than 50% employed swarm intelligence and evolutionary algorithms to solve the complex scheduling problems. This paper aims to provide a comprehensive literature review of production scheduling for intelligent manufacturing systems with the energy-related constraints and objectives. The main goals are to summarize, analyze, discuss, and synthesize the existing achievements, current research status, and ongoing studies, and to give useful insight into future research, especially intelligent strategies for solving the energy-efficient scheduling problems. The scope of this review is focused on the journal publications of the Web of Science database. The energy efficiency-related publications are classified and analyzed according to five criteria. Then, the research trends of energy efficiency are discussed. Finally, some directions are pointed out for future studies.

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.

scholarly journals The Role of Structural Context in Making Business Sense of Investments for Sustainability–A Case Study

2020 ◽  
Vol 12 (17) ◽  
pp. 7006
Author(s):  
Josefine Rasmussen
Keyword(s):  
Decision Making ◽  
Energy Efficiency ◽  
Investment Decision ◽  
Sustainable Manufacturing ◽  
Manufacturing Companies ◽  
Improve Energy Efficiency ◽  
Structural Context ◽  
Investment Decision Making

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.

Modelling and Design of Closed-Loop Manufacturing Systems

2013 ◽  
Vol 378 ◽  
pp. 367-374 ◽  
Author(s):  
Andrey A. Kutin ◽  
Mikhail Turkin
Keyword(s):  
Analytical Method ◽  
Flexible Manufacturing ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Flexible Manufacturing System ◽  
Closed Loop ◽  
Production Systems ◽  
Finite Buffers ◽  
Unreliable Machines

This paper introduces an analytical method for evaluating the performance of closed loop manufacturing systems with unreliable machines and finite buffers. The method involves transforming an arbitrary loop into one without thresholds and then evaluating the transformed loop using a new set of decomposition equations. It is more accurate than existing methods and is effective for a wider range of cases. The convergence reliability, and speed of the method are also discussed. In addition, observations are made on the behavior of closed loop production systems under various conditions. Finally, the method is used in a case study to design a flexible manufacturing system for production of aerospace parts.

scholarly journals Technical, economic, and environmental performance assessment of manufacturing systems: The Multi-layer Enterprise Input-Output formalisation method

2021 ◽  
Author(s):  
Claudio Castiglione ◽  
Erica Pastore ◽  
Arianna Alfieri
Keyword(s):  
Environmental Performance ◽  
Lean Manufacturing ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Sustainable Manufacturing ◽  
Flow Analysis ◽  
Material Flow Analysis ◽  
Value Added ◽  
Economic Assessment ◽  
Input Output

In production planning and control, assessing the performance of a manufacturing system is a multi-dimensional problem, in which neglected dimensions may lead to hidden inefficiencies and missed opportunities for gaining a competitive advantage. This paper proposes a data formalisation method to model a manufacturing system by simultaneously considering value creation and technical, economic, and environmental performance. The proposed method combines the techno-economic assessment of lean manufacturing and sustainable manufacturing with the data-driven approach, typical of Industry 4.0, to overcome the limitations of the lean approaches in addressing complex systems. The method is based on integrating Multi-layer Stream Mapping and a combination of Enterprise Input-Output and Material Flow Analysis. It also considers non-value-added activities such as transport and inventories. Pen and papers and digital approaches can simultaneously exploit the method as a shared architecture for formal data integration. The implementation of the method is shown through a numerical example based on a recycled plastic pipeline manufacturing system.

SYSTEMATIZATION OF INTERNATIONAL AND DOMESTIC EXPERIENCE IN PROJECT MANAGEMENT AIMED AT ADAPTING PUBLIC-PRIVATE PARTNERSHIPS TO THE IMPLEMENTATION OF SUSTAINABLE ENERGY DEVELOPMENT PROGRAMS

2021 ◽  
pp. 42-54
Author(s):  
I. Chupryna ◽  
R. Tormosov ◽  
K. Chupryna ◽  
M. Oleksandr ◽  
P. Natali
Keyword(s):  
Energy Efficiency ◽  
Project Management ◽  
Large Scale ◽  
Public Private Partnership ◽  
Public Private Partnerships ◽  
Development Programs ◽  
Economic Stability ◽  
Private Partnership ◽  
Improve Energy Efficiency ◽  
Energy Independence

European countries are recognized leaders in the use of public-private partnerships in project management for large-scale infrastructure projects, including those that contribute to energy efficiency in various sectors of the economy. Their experience is a useful example for Ukraine in its quest for energy independence and economic stability. Establishing partnerships with business will increase the resources of the state and promote the involvement of the private sector in the implementation of profitable and image projects for both stakeholders. The development of mechanisms and recommendations for the development of public-private partnership (PPP) should be preceded by an analysis of international experience in creating a favorable and attractive environment in which public-private partnerships can be intensified. Since energy efficiency is the key to the successful functioning of the economy of any state, it is necessary, creating the conditions for the successful functioning of public-private partnership, to develop programs and projects to improve energy efficiency, which will be implemented under the PPP on a priority basis.

Towards a Digital Depot to Support Sustainable Manufacturing During Crisis Response

2021 ◽  
Author(s):  
Nancy Diaz-Elsayed ◽  
K. C. Morris ◽  
Julius Schoop
Keyword(s):  
Manufacturing Systems ◽  
Production Systems ◽  
Sustainable Manufacturing ◽  
Crisis Response ◽  
Manufacturing Operations ◽  
Level Data ◽  
Equipment Testing ◽  
Sustainability Challenges ◽  
And Shifts ◽  
Future Work

Abstract The COVID-19 pandemic has imposed new challenges to maintaining sustainability in our manufacturing operations. With such high variability in demand for urgently needed products (e.g., personal protective equipment, testing technologies) and shifts in the needed capabilities of already complex production systems, sustainability challenges concerning waste management, life cycle impact characterization, and production operations have come to light. An extensive amount of data can be extracted from manufacturing systems, but it is not yet being used to improve the performance of production systems and maintain sustainability strategies during times of distress. This article proposes the concept of a Digital Depot. Being virtual in nature, the depot can contain plans and data for many different types of crises and contain a wider array of products than would be available in a physical, national stockpile. The information could be made available on demand to a national base of manufacturers to help them swiftly pivot to the production of critically needed goods while building on their existing manufacturing capabilities. The contents of the Digital Depot would be applicable to several stages pertinent to manufacturing operations including product definition, production planning information, asset and factory-level data, as well as data concerning the supply chain, distribution, and end-of-life stages. Future work is recommended in the development of templates for robust and secure data sharing, as well as multi-disciplinary identification of businesses cases for data-driven collaborative and sustainable manufacturing practices enabled by the Digital Depot.

Performance analysis of CyberManufacturing Systems

2017 ◽  
Vol 233 (5) ◽  
pp. 1362-1376 ◽  
Author(s):  
Zhengyi Song ◽  
Young Moon
Keyword(s):  
Performance Analysis ◽  
Manufacturing Systems ◽  
Fog Computing ◽  
Sustainable Manufacturing ◽  
System Level ◽  
Self Awareness ◽  
Component Level ◽  
Fully Integrated ◽  
Simulation Techniques ◽  
Recent Developments

CyberManufacturing System is an advanced vision for future manufacturing where physical components are fully integrated and seamlessly networked with computational processes, forming an on-demand, intelligent, and communicative manufacturing resource and capability repository with optimal and sustainable manufacturing solutions. The CyberManufacturing System utilizes recent developments in Internet of things, cloud computing, fog computing, service-oriented technologies, among others. Manufacturing resources and capabilities can be encapsulated, registered, and connected to each other directly or through the Internet, thus enabling intelligent behaviors of manufacturing components and systems such as self-awareness, self-prediction, self-optimization, and self-configuration. This research presents an introduction to the CyberManufacturing System, establishing the architecture and functions of the CyberManufacturing System, designing the pivotal control strategy, and investigating the performance analysis of the CyberManufacturing System using modeling and simulation techniques. In total, five component-level examples and one system-level case study have been developed and used for illustration and validation of the CyberManufacturing System operations. The results show that the CyberManufacturing System is superior to other types of manufacturing systems in terms of functionality and cooperative performance.

scholarly journals Analysis of the Impact of Residential Property and Equipment on Building Energy Efficiency and Consumption—A Data Mining Approach

2020 ◽  
Vol 10 (10) ◽  
pp. 3589 ◽  
Author(s):  
Mahsa Nazeriye ◽  
Abdorrahman Haeri ◽  
Francisco Martínez-Álvarez
Keyword(s):  
Data Mining ◽  
Energy Efficiency ◽  
Energy Consumption ◽  
Large Scale ◽  
Building Energy Efficiency ◽  
Data Set ◽  
Residential Homes ◽  
Improve Energy Efficiency ◽  
Data Mining Approach ◽  
The Impact

Human living could become very difficult due to a lack of energy. The household sector plays a significant role in energy consumption. Trying to optimize and achieve efficient energy consumption can lead to large-scale energy savings. The aim of this paper is to identify the equipment and property affecting energy efficiency and consumption in residential homes. For this purpose, a hybrid data-mining approach based on K-means algorithms and decision trees is presented. To analyze the approach, data is modeled once using the approach and then without it. A data set of residential homes of England and Wales is arranged in low, medium and high consumption clusters. The C5.0 algorithm is run on each cluster to extract factors affecting energy efficiency. The comparison of the modeling results, and also their accuracy, prove that the approach employed has the ability to extract the findings with greater accuracy and detail than in other cases. The installation of boilers, using cavity walls, and installing insulation could improve energy efficiency. Old homes and the usage of economy 7 electricity have an unfavorable effect on energy efficiency, but the approach shows that each cluster behaved differently in these factors related to energy efficiency and has unique results.

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