Job shop schedules analysis in the context of industry 4.0

2017 ◽  
Author(s):  
R. A. Sousa ◽  
M. L. R. Varela ◽  
C. Alves ◽  
J. Machado
Keyword(s):  
Industry 4.0 ◽  
Job Shop

One-of-a-kind Production in Cyber-Physical Production Systems Considering Machine Failures

2021 ◽  
pp. 1-20
Author(s):  
Guido Vinci Carlavan ◽  
Daniel Alejandro Rossit
Keyword(s):  
Industry 4.0 ◽  
Information Technologies ◽  
Job Shop ◽  
Production Systems ◽  
Dispatching Rules ◽  
Shop Floor ◽  
Due Dates ◽  
Efficient Manner ◽  
Large Variability ◽  
Cyber Physical Production Systems

Industry 4.0 proposes the incorporation of information technologies at all levels of the production process. By incorporating these technologies, Industry 4.0 provides new tools for production planning processes, allowing to address problems in an innovative and efficient manner. From these technologies and tools, it is that in this work a One-of-a-Kind Production (OKP) process is approached, where the products tend to be highly customized. OKP implies working with a very large variability within production, demanding very efficient planning systems. For this, a planning model based on CONWIP-type strategies was proposed, which seeks to level the production of a shop floor configured in the form of a job shop. Even more, for having a more realistic shop-floor representation, machine failures have been included in the model. In turn, different dispatching rules were proposed to study the performance and analyze the behaviour of the system. From the results obtained, it is observed that, when the production demand is very exigent in relation with the capacity of the system, the dispatching rules that analyze the workload generated by each job tend to perform better. However, when the demand on the capacity of the production system is less intense, the rules associated with due dates are the ones that obtain the best results.

scholarly journals Solving the Job-Shop Scheduling Problem in the Industry 4.0 Era

Technologies ◽  
2018 ◽  
Vol 6 (4) ◽  
pp. 107 ◽  
Author(s):  
Matheus Leusin ◽  
Enzo Frazzon ◽  
Mauricio Uriona Maldonado ◽  
Mirko Kück ◽  
Michael Freitag
Keyword(s):  
Industry 4.0 ◽  
Data Exchange ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Intelligent System ◽  
Scheduling Problem ◽  
Job Shop Scheduling Problem ◽  
Multi Agent Systems ◽  
Time Data ◽  
Shop Scheduling

Technological developments along with the emergence of Industry 4.0 allow for new approaches to solve industrial problems, such as the Job-shop Scheduling Problem (JSP). In this sense, embedding Multi-Agent Systems (MAS) into Cyber-Physical Systems (CPS) is a highly promising approach to handle complex and dynamic JSPs. This paper proposes a data exchange framework in order to deal with the JSP considering the state-of-the-art technology regarding MAS, CPS and industrial standards. The proposed framework has self-configuring features to deal with disturbances in the production line. This is possible through the development of an intelligent system based on the use of agents and the Internet of Things (IoT) to achieve real-time data exchange and decision making in the job-shop. The performance of the proposed framework is tested in a simulation study based on a real industrial case. The results substantiate gains in flexibility, scalability and efficiency through the data exchange between factory layers. Finally, the paper presents insights regarding industrial applications in the Industry 4.0 era in general and in particular with regard to the framework implementation in the analyzed industrial case.

scholarly journals Review of job shop scheduling research and its new perspectives under Industry 4.0

2017 ◽  
Vol 30 (4) ◽  
pp. 1809-1830 ◽  
Author(s):  
Jian Zhang ◽  
Guofu Ding ◽  
Yisheng Zou ◽  
Shengfeng Qin ◽  
Jianlin Fu
Keyword(s):  
Industry 4.0 ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Shop Scheduling

scholarly journals Optimization of the Job Shop Scheduling Problem in Industry 4.0

2020 ◽  
Vol 26 (1) ◽  
pp. 13-18
Author(s):  
Olga Ristić ◽  
Marjan Milošević ◽  
Sandra Milunović-Koprivica ◽  
Milan Vesković ◽  
Veljko Aleksić
Keyword(s):  
Industry 4.0 ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Scheduling Problem ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling

scholarly journals A Critical Analysis of Job Shop Scheduling in Context of Industry 4.0

2021 ◽  
Vol 13 (14) ◽  
pp. 7684
Author(s):  
Raja Awais Liaqait ◽  
Shermeen Hamid ◽  
Salman Sagheer Warsi ◽  
Azfar Khalid
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Industry ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Intelligent Manufacturing ◽  
Distributed Scheduling ◽  
Lead Times ◽  
Shop Scheduling ◽  
Third Phase ◽  
Customized Production

Scheduling plays a pivotal role in the competitiveness of a job shop facility. The traditional job shop scheduling problem (JSSP) is centralized or semi-distributed. With the advent of Industry 4.0, there has been a paradigm shift in the manufacturing industry from traditional scheduling to smart distributed scheduling (SDS). The implementation of Industry 4.0 results in increased flexibility, high product quality, short lead times, and customized production. Smart/intelligent manufacturing is an integral part of Industry 4.0. The intelligent manufacturing approach converts renewable and nonrenewable resources into intelligent objects capable of sensing, working, and acting in a smart environment to achieve effective scheduling. This paper aims to provide a comprehensive review of centralized and decentralized/distributed JSSP techniques in the context of the Industry 4.0 environment. Firstly, centralized JSSP models and problem-solving methods along with their advantages and limitations are discussed. Secondly, an overview of associated techniques used in the Industry 4.0 environment is presented. The third phase of this paper discusses the transition from traditional job shop scheduling to decentralized JSSP with the aid of the latest research trends in this domain. Finally, this paper highlights futuristic approaches in the JSSP research and application in light of the robustness of JSSP and the current pandemic situation.

scholarly journals Smart cyber-physical production system enabled workpiece production in digital twin job shop

2021 ◽  
Vol 13 (9) ◽  
pp. 168781402110408
Author(s):  
Wang Chuang ◽  
Zhou Guanghui ◽  
Wu Junsheng
Keyword(s):  
Production System ◽  
Industry 4.0 ◽  
Job Shop ◽  
Interaction Model ◽  
Machining Processes ◽  
Digital Twin ◽  
Future Production ◽  
Manufacturing Resources ◽  
Level Production ◽  
Process Level

Industry 4.0 describes the future production of workpiece in job shop as: the workpiece is a smart one; it knows the details of how to manufacture itself; and it can communicate with manufacturing environment to support its own machining processes. This means that the production of workpiece places more emphasis on the smart realization of the process level in Industry 4.0. However, how to implement the production scenario based on existing technologies has not yet been well studied. On account of this, this article aims to study how to use existing technologies in job shop such as digital twins, Internet of Things (IoT), Cyber-physical Production System (CPPS), etc., to realize the workpiece-driven process-level production. The process-level production of a workpiece is divided into three stages according to the different manufacturing resources involved. On this basis, the production of the workpiece in digital twin job shop is divided into process level, operation level, and IoT/sensor level. Firstly, the manufacturing requirements at process level are generated according to production planning and process sheet. And these requirements are written into RFID tag of the workpiece. The workpiece dynamically interacts with different workstations via RFID reader/antenna in order to complete the manufacturing requirements. Secondly, based on the tag data, the interaction model of operation level, and IoT/sensor level CPPSs is given. Thirdly, at IoT/sensor level, the RFID devices are treated as a CPPS to track the manufacturing resources. And different smart sensors are used as independent sensor CPPSs to monitor the running status of machine tool. The RFID and sensor CPPSs are triggered by operation level CPPSs. Finally, a digital twin job shop is taken as an example to illustrate the feasibility of the proposed models and methods.

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