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.

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.

scholarly journals An Analysis of Research Trends in the Sustainability of Production Palnning

Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 483
Author(s):  
Mohamed Saeed khaled ◽  
Ibrahim Abdelfadeel Shaban ◽  
Ahmed Karam ◽  
Mohamed Hussain ◽  
Ismail Zahran ◽  
...  
Keyword(s):  
Production Planning ◽  
Production Scheduling ◽  
Production Systems ◽  
Lot Sizing ◽  
Raw Materials ◽  
Social Indicators ◽  
Sustainable Production ◽  
Future Research ◽  
Scheduling Problems ◽  
Planning Problems

Sustainability has become of great interest in many fields, especially in production systems due to the continual increase in the scarcity of raw materials and environmental awareness. Recent literature has given significant attention to considering the three sustainability pillars (i.e., environmental, economic, and social sustainability) in solving production planning problems. Therefore, the present study conducts a review of the literature on sustainable production planning to analyze the relationships among different production planning problems (e.g., scheduling, lot sizing, aggregate planning, etc.) and the three sustainability pillars. In addition, we analyze the identified studies based on the indicators that define each pillar. The results show that the literature most frequently addresses production scheduling problems while it lacks studies on aggregate production planning problems that consider the sustainability pillars. In addition, there is a growing trend towards obtaining integrated solutions of different planning problems, e.g., combining production planning problems with maintenance planning or energy planning. Additionally, around 45% of the identified studies considered the integration of the economic and the environmental pillars in different production planning problems. In addition, energy consumption and greenhouse gas emissions are the most frequent sustainability indicators considered in the literature, while less attention has been given to social indicators. Another issue is the low number of studies that have considered all three sustainability pillars simultaneously. The finidings highlight the need for more future research towards holistic sustainable production planning approaches.

A Review of Multi Agent based Production Scheduling in Manufacturing System

2020 ◽  
Vol 14 ◽  
Author(s):  
Om Ji Shukla ◽  
Gunjan Soni ◽  
Rajesh Kumar ◽  
Rashpal S. Ahluwalia
Keyword(s):  
Production Scheduling ◽  
Global Economy ◽  
Manufacturing Systems ◽  
Manufacturing Sector ◽  
Local Economy ◽  
Future Research ◽  
Scheduling Problems ◽  
Key Issues ◽  
Multi Agent ◽  
Traditional Approaches

Backgrounds: The manufacturing sector has seen dynamic changes during the last few years, namely the move from product-oriented local economy to customer-driven global economy. In this environment, manufacturing systems have been required to deliver highly flexible, demand-driven and customized products. Hence, multi agent system (MAS) technology can play an important role in making highly responsive production scheduling systems in order to meet dynamic and uncertain changes in demand. Methods: This paper offers a review of MAS for production scheduling problems in manufacturing systems. The objective of the paper is twofold. First, it describes traditional and MAS based approaches for different production scheduling problems and presents advantages of MAS over traditional approaches. Second, it aims to review different MAS platforms and evaluate some key issues involved in MAS based production scheduling. Results: A variety of different MAS applications in production scheduling is reviewed in four categories of key issues: agent encapsulation, agent organization, agent coordination & negotiation and agent learning. Conclusion: Finally, this review presents a conceptual framework to implement MAS in production scheduling and also highlights the future research opportunities as well as challenges.

scholarly journals Energy-Efficient Hybrid Routing Protocol for IoT Communication Systems in 5G and Beyond

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 537
Author(s):  
Mohammad Baniata ◽  
Haftu Tasew Reda ◽  
Naveen Chilamkurti ◽  
Alsharif Abuadbba
Keyword(s):  
Energy Efficiency ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Communication Systems ◽  
Multiple Input Multiple Output ◽  
Sensor Nodes ◽  
Clustering Methods ◽  
Mimo Antenna ◽  
Improve Energy Efficiency ◽  
Art Research

One of the major concerns in wireless sensor networks (WSNs) is most of the sensor nodes are powered through limited lifetime of energy-constrained batteries, which majorly affects the performance, quality, and lifetime of the network. Therefore, diverse clustering methods are proposed to improve energy efficiency of the WSNs. In the meantime, fifth-generation (5G) communications require that several Internet of Things (IoT) applications need to adopt the use of multiple-input multiple-output (MIMO) antenna systems to provide an improved capacity over multi-path channel environment. In this paper, we study a clustering technique for MIMO-based IoT communication systems to achieve energy efficiency. In particular, a novel MIMO-based energy-efficient unequal hybrid clustering (MIMO-HC) protocol is proposed for applications on the IoT in the 5G environment and beyond. Experimental analysis is conducted to assess the effectiveness of the suggested MIMO-HC protocol and compared with existing state-of-the-art research. The proposed MIMO-HC scheme achieves less energy consumption and better network lifetime compared to existing techniques. Specifically, the proposed MIMO-HC improves the network lifetime by approximately 3× as long as the first node and the final node dies as compared with the existing protocol. Moreover, the energy that cluster heads consume on the proposed MIMO-HC is 40% less than that expended in the existing protocol.

Energy Efficient Multi-Hop Wireless Sensor Networks with CMIMO-SM Scheme

2014 ◽  
Vol 666 ◽  
pp. 322-326
Author(s):  
Yu Yang Peng ◽  
Jae Ho Choi
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Optimal Number ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Improve Energy Efficiency ◽  
Output System

Energy efficiency is one of the important hot issues in wireless sensor networks. In this paper, a multi-hop scheme based on a cooperative multi-input multi-outputspatial modulation technique is proposed in order to improve energy efficiency in WSN. In this scheme, the sensor nodes are grouped into clusters in order to achieve a multi-input multi-output system; and a simple forwarding transmission scenario is considered so that the intermediate clusters only forward packets originated from the source cluster down to the sink cluster. In order to verify the performance of the proposed system, the bit energy consumption formula is derived and the optimal number of hopsis determined. By qualitative experiments, the obtained results show that the proposed scheme can deliver the data over multiple hops consuming optimal energy consumption per bit.

scholarly journals Adaptive Framework Combining Sensors and IoT for Data Monitoring in Restricted Areas

2019 ◽  
Vol 8 (11) ◽  
pp. 564-567 ◽  
Keyword(s):  
Energy Efficiency ◽  
Data Transmission ◽  
Energy Efficient ◽  
Data Transfer ◽  
Sensor Data ◽  
Data Monitoring ◽  
Security Measures ◽  
Improve Energy Efficiency ◽  
Location Data ◽  
Adaptive Framework

The deployment of Internet-of-Things (IoT) enables an even richer variety of sensors at a much larger scale. Where offloading both the evaluation and the polling of IoT sensor data to the cloud would improve energy efficiency and data transfer costs for the mobile. We build an energy efficient framework for Combining Sensors and IoT to help developers easily builds applications that evaluate sensor data on the server via data transmission. We built a advanced framework to compress data i.e Novel Data Compression Approach that helps the user to know the regular movement of particular person with the sensor within the limited premises and the location surveillance of the host will be saving the location data with some security measures We also implement our protocol and compare it with the certificate-based scheme to illustrate its feasibility.

scholarly journals Scheduling and Rescheduling Operations Using Decision Support Systems: Insights From Emotional Influences on Decision-Making

2021 ◽  
Vol 2 ◽  
Author(s):  
Mélody Mailliez ◽  
Olga Battaïa ◽  
Raphaëlle N. Roy
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Mental State ◽  
Production Scheduling ◽  
Manufacturing Systems ◽  
Support Systems ◽  
Mental States ◽  
Future Research ◽  
Modern Manufacturing

For many years, manufacturers have focused on improving their productivity. Production scheduling operations are critical for this objective. However, in modern manufacturing systems, the original schedule must be regularly updated as it takes places in a dynamic and uncertain environment. The modern manufacturing environment is therefore very stressful for the managers in charge of the production process because they have to cope with many disruptions and uncertainties. To help them in their decision-making process, several decision support systems (DSSs) have been developed. A recent and enormous challenge is the implementation of DSSs to efficiently manage the aforementioned issues. Nowadays, these DSSs are assumed to reduce the users' stress and workload because they automatically (re)schedule the production by applying algorithms. However, to the best of our knowledge, the reciprocal influence of users' mental state (i.e., cognitive and affective states) and the use of these DSSs have received limited attention in the literature. Particularly, the influence of users' unrelated emotions has received even less attention. However, these influences are of particular interest because they can account for explaining the efficiency of DSSs, especially in modulating DSS feedback processing. As a result, we assumed that investigating the reciprocal influences of DSSs and users' mental states could provide useful avenues of investigation. The intention of this article is then to provide recommendations for future research on scheduling and rescheduling operations by suggesting the investigation of users' mental state and encouraging to conduct such research within the neuroergonomic approach.

scholarly journals How environment dynamics affects production scheduling: Requirements for development of CPPS models

2021 ◽  
Vol 49 (4) ◽  
pp. 827-834
Author(s):  
Cátia Alves ◽  
Goran Putnik ◽  
Leonilde Varela
Keyword(s):  
Production Scheduling ◽  
Manufacturing Systems ◽  
New Technologies ◽  
Production Systems ◽  
Strong Positive Correlation ◽  
Systems Architecture ◽  
Study Results ◽  
Cyber Physical Production Systems ◽  
Scheduling Models

Production scheduling can be affected by many disturbances in the manufacturing system, and consequently, the feasible schedules previously defined became obsolete. Emerging of new technologies associated with Industry 4.0, such as Cyber-Physical Production Systems, as a paradigm of implementation of control and support in decision making, should embed the capacity to simulate different environment scenarios based on the data collected by the manufacturing systems. This paper presents the evaluation of environment dynamics effect on production scheduling, considering three scheduling models and three environment scenarios, through a case study. Results show that environment dynamics affect production schedules, and a very strong or strong positive correlation between environment dynamics scenarios and total completion time with delay, over three scheduling paradigms. Based on these results, the requirement for mandatory inclusion of a module for different environment dynamics scenarios generation and the corresponded simulations, of a Cyber-Physical Production Systems architecture, is confirmed.

scholarly journals A COMPARATIVE STUDY OF THE USABILITY OF DIFFERENT PRODUCTION SCHEDULING ALGORITHMS AND RULES

2021 ◽  
Vol 2 ◽  
pp. 41-46
Author(s):  
Pavol Jurík
Keyword(s):  
Production Process ◽  
Production Scheduling ◽  
Job Shop ◽  
Flow Shop ◽  
Production Systems ◽  
Scheduling Problems ◽  
History Of ◽  
Service Object ◽  
The Right ◽  
Production Plans

Production scheduling optimization is a very important part of a production process. There are production systems with one service object and systems with multiple service objects. When using several service objects, there are systems with service objects arranged in a parallel or in a serial manner. We also distinguish between systems such as flow shop, job shop, open shop and mixed shop. Throughout the history of production planning, a number of algorithms and rules have been developed to calculate optimal production plans. These algorithms and rules differ from each other in the possibilities and conditions of their application. Since there are too many possible algorithms and rules it is not easy to select the proper algorithm or rule for solving a specific scheduling problem. In this article we analyzed the usability of 33 different algorithms and rules in total. Each algorithm or rule is suitable for a specific type of problem. The result of our analysis is a set of comparison tables that can serve as a basis for making the right decision in the production process decision-making process in order to select the proper algorithm or rule for solving a specific problem. We believe that these tables can be used for a quick and easy selection of the proper algorithm or rule for solving some of the typical production scheduling problems.

scholarly journals Energy Losses Due to Imperfect Payment Infrastructure and Payment Instruments

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8213
Author(s):  
Oleksandr Melnychenko
Keyword(s):  
Energy Efficiency ◽  
Energy Cost ◽  
Negative Impact ◽  
The European Union ◽  
Strategic Objectives ◽  
Improve Energy Efficiency ◽  
Cost Of Energy ◽  
Using Data ◽  
The Impact ◽  
Number Of Customers

One of the strategic objectives of the European Union is a reduction in greenhouse gas emissions and improvement of energy efficiency by at least 32.5% in different areas of the economy by 2030. However, little is known about the impact of payment in retail on energy consumption. The purpose of this paper is to assess the chain of losses of time and energy, and therefore financial losses, that occur due to the imperfection of payment infrastructure and instruments using data of cashiers’ working time. The research is based on a regression analysis method, where the energy cost per payment transaction is considered in this study as a function of the number of customers per hour and the energy cost. The results of the panel models highlight that the number of customers per hour has a negative impact on the cost of energy per payment transaction. Furthermore, modern means and methods of payment, including cryptocurrencies, do not solve the problem of the excessive time that it takes to service payments, which entails a waste of energy and money. The empirical results give valuable insights into how to best organise payment in retail to achieve lower energy costs and improve energy efficiency in payment infrastructure.

Sign in / Sign up

Export Citation Format

Share Document