scholarly journals Novel Complexity Indicator of Manufacturing Process Chains and Its Relations to Indirect Complexity Indicators

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Vladimir Modrak ◽  
Zuzana Soltysova
Keyword(s):  
Manufacturing Process ◽  
Material Flow ◽  
Manufacturing Systems ◽  
Job Shop ◽  
Flow Shop ◽  
Manufacturing Processes ◽  
Process Chains

Manufacturing systems can be considered as a network of machines/workstations, where parts are produced in flow shop or job shop environment, respectively. Such network of machines/workstations can be depicted as a graph, with machines as nodes and material flow between the nodes as links. The aim of this paper is to use sequences of operations and machine network to measure static complexity of manufacturing processes. In this order existing approaches to measure the static complexity of manufacturing systems are analyzed and subsequently compared. For this purpose, analyzed competitive complexity indicators were tested on two different manufacturing layout examples. A subsequent analysis showed relevant potential of the proposed method.

And The World Came To See: New Manufacturing System Designs and Industrial Revolutions

2002 ◽  
Author(s):  
J. T. Black ◽  
David S. Cochran
Keyword(s):  
System Design ◽  
Systems Engineering ◽  
Lean Manufacturing ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Job Shop ◽  
Flow Shop ◽  
The World ◽  
Industrial Revolutions ◽  
New System

AND THE WORLD CAME TO SEE. When a new manufacturing system design (MSD) is developed by a company or a group of companies, the rest of the world comes to those factories to learn about the new system. In the last 200 years, three new factory designs have evolved, called the job shop, the flow shop and the lean shop. Each is based on a new system design — a functional design, a product flow design and a linked cell design. New factory designs lead to new industrial leaders and even new industrial revolutions (IR’s). Two appendixes are included: One outlines the implementation strategy for the lean shop and the other is a discussion of lean manufacturing from the viewpoint of K. Hitomi, Japanese professor of manufacturing systems engineering.

Deadlock Prevention in Manufacturing Systems With AGV Systems: Banker’s Algorithm Approach

1997 ◽  
Vol 119 (4B) ◽  
pp. 849-854 ◽  
Author(s):  
Chang Wan Kim ◽  
J. M. A. Tanchoco ◽  
Pyung-Hoi Koo
Keyword(s):  
Material Flow ◽  
Manufacturing Systems ◽  
Job Shop ◽  
Deadlock Prevention ◽  
Job Shops ◽  
Vehicle Systems ◽  
Problems And Solutions ◽  
Handling Methods ◽  
Banker's Algorithm ◽  
Agv Systems

An important issue in the operational control of an automated job shop is the prevention and resolution of shop deadlocks. In this paper, we discuss the problems and solutions of deadlocks in manufacturing systems with automated guided vehicle systems, describe a banker’s algorithm for the control of material flow in job shops, and present the results of simulation experiments to compare the performance of several deadlock handling methods.

A Desktop Application for Sustainability Performance Assessment of Composed Unit-Based Manufacturing Systems

2017 ◽  
Author(s):  
Matteo M. Smullin ◽  
Zahra Iman ◽  
Karl R. Haapala
Keyword(s):  
Manufacturing Process ◽  
Manufacturing Systems ◽  
Sustainability Assessment ◽  
Information Modeling ◽  
Process Models ◽  
System Level ◽  
Manufacturing Processes ◽  
Modeling Framework ◽  
Process Flow ◽  
Desktop Application

Life cycle assessment software packages such as SimaPro, GaBi, and Umberto have become well-established tools for conducting environmental impact analysis. However, applications for broader sustainability assessment are limited. Recent research has developed an information modeling framework to compose models of unit manufacturing processes for sustainability assessment and has led to the definition of unit manufacturing process information modeling concepts. An engineer can use the framework to conduct manufacturing system-level sustainability assessments by composing models of unit manufacturing processes. Assessment results can aid engineers in selecting the superior manufacturing process flow for a given product. To demonstrate usefulness of the information framework, a prototype desktop application has been developed. The application was implemented in Windows Project Foundation (WPF) using C# as the coding language to create a graphical user interface. Mathworks MATLAB serves as the calculation engine. Unit manufacturing process models follow the framework and are read by the application, which produces a sustainability assessment for the manufacturing process flow. A manufacturing process flow for an automobile-like metal product acts is used to demonstrate the software application.

Assembly and Disassembly via Automation Tools

2011 ◽  
Vol 467-469 ◽  
pp. 2066-2071
Author(s):  
Angela Javorova ◽  
Erika Hrušková ◽  
Karol Velíšek
Keyword(s):  
Manufacturing Process ◽  
Material Flow ◽  
Manufacturing Systems ◽  
International Institutions ◽  
Materials Science ◽  
Applied Mechanics ◽  
Assembly Cell ◽  
Automated Separation ◽  
Automation Tools ◽  
Automated Disassembly

Assembly and disassembly is a new and also a rapid developed trend in manufacturing area. In the future the assembly and disassembly will be one inseparable part of manufacturing process. Especially automated disassembly is a technology, which is trying to satisfy needs and requirements. Many of special requirements are supported by international institutions, research programs and foundations. In our Institute of Manufacturing Systems and Applied Mechanics at Faculty of Materials Science and Technology the project named Intelligent assembly cell is realized. Within the frame of this project designing of structure, following of several assembly steps, organization of material flow and others is processed. Currently disassembly is one part of solving problems as assembly. Automated disassembly technique allows an automated separation of various parts, from which was disassembled product created.

Maintenance on Job Shop Industry: Review and Analysis

2016 ◽  
Vol 842 ◽  
pp. 365-372 ◽  
Author(s):  
Herman Budi Harja ◽  
Tri Prakosa ◽  
Yatna Yuwana Martawirya
Keyword(s):  
Manufacturing Systems ◽  
Job Shop ◽  
Flow Shop ◽  
Dynamic Condition ◽  
Maintenance Optimization ◽  
Reliability Growth ◽  
Monitoring Cost ◽  
Reliability Modeling ◽  
Maintenance Schedule ◽  
Reliability Improvement

This paper presents overviews about reliability and maintainability of equipment especially for job-shop manufacturing systems. The job shop industry has the characteristics of a more dynamic production than flow shop industries, where products with a variety of great but small amounts. Its dynamic condition certainly contributes directly to the failure rate and reliability growth of equipment. Therefore, proper maintenance should be done as the reliability improvement. Stages of reliability improvement are reliability modeling, reliability analysis and maintenance optimization. This stage is based on reliability growth of equipment that is indicated the deterioration process of failure components, it can be build from maintenance data history or condition data monitoring.. Cost is often considered in points of a maintenance schedule. This cost was affected by minimizing the negative effects of maintenance and maximizing the benefit of production. The attention at reliability and maintenance optimization is a well researches area until now. This paper presents a brief review of existing reliability and maintenance research. Several reliable methods in this area are discussed and maintenance on job-shop industry as future prospects is investigated. It is shown in this paper that some aspect in the area of maintenance on job-shop industry steel needs to be deeply developed.

Modeling and Analyzing the Material Flow of Crowdsourcing Processes in Cloud-Based Manufacturing Systems Using Stochastic Petri Nets

2014 ◽  
Author(s):  
Dazhong Wu ◽  
David W. Rosen ◽  
Dirk Schaefer
Keyword(s):  
Petri Nets ◽  
Material Flow ◽  
Manufacturing Systems ◽  
Cloud Manufacturing ◽  
Stochastic Petri Nets ◽  
Manufacturing Processes ◽  
Manufacturing Enterprises ◽  
Car Suspension ◽  
Manufacturing Performance

Cloud-based manufacturing (CBM), also referred to as cloud manufacturing, has the potential to allow manufacturing enterprises to be rapidly scaled up and down by crowdsourcing manufacturing tasks or sub-tasks. To improve the efficiency of the crowdsourcing process, the material flow of CBM systems needs to be managed so that several manufacturing processes can be executed simultaneously. Further, the scalability of manufacturing capacity in CBM needs to be designed, analyzed, and planned in response to rapidly changing market demands. The objective of this paper is to introduce a stochastic petri nets (SPNs)-based approach for modeling and analyzing the concurrency and synchronization of the material flow in CBM systems. The proposed approach is validated through a case study of a car suspension module. Our results have shown that the SPN-based approach helps analyze the structural and behavioral properties of a CBM system and verify manufacturing performance.

Production Planning Models using Max-Plus Algebra

2013 ◽  
pp. 227-257 ◽  
Author(s):  
Arun N. Nambiar ◽  
Aleksey Imaev ◽  
Robert P. Judd ◽  
Hector J. Carlo
Keyword(s):  
Manufacturing Systems ◽  
Stochastic Systems ◽  
Performance Metrics ◽  
Job Shop ◽  
Flow Shop ◽  
Linear Equations ◽  
Building Blocks ◽  
Buffer Allocation ◽  
Planning Models ◽  
Machining Operations

The chapter presents a novel building block approach to developing models of manufacturing systems. The approach is based on max-plus algebra. Within this algebra, manufacturing schedules are modeled as a set of coupled linear equations. These equations are solved to find performance metrics such as the make span. The chapter develops a generic modeling block with three inputs and three outputs. It is shown that this structure can model any manufacturing system. It is also shown that the structure is hierarchical, that is, a set of blocks can be reduced to a single block with the same three inputs and three output structure. Basic building blocks, like machining operations, assembly, and buffering are derived. Job shop, flow shop, and cellular system applications are given. Extensions of the theory to buffer allocation and stochastic systems are also outlined. Finally, several numerical examples are given throughout the development of the theory.

DYNAMIC SCHEDULING OF MANUFACTURING SYSTEMS WITH MACHINE LEARNING

2001 ◽  
Vol 12 (06) ◽  
pp. 751-762 ◽  
Author(s):  
PAOLO PRIORE ◽  
DAVID DE LA FUENTE ◽  
ALBERTO GOMEZ ◽  
JAVIER PUENTE
Keyword(s):  
Machine Learning ◽  
Manufacturing Systems ◽  
Job Shop ◽  
Dynamic Scheduling ◽  
Flow Shop ◽  
Dispatching Rules ◽  
Heuristic Rules ◽  
Learning Program ◽  
Training Examples ◽  
Definition Of

A common way of scheduling jobs dynamically in a manufacturing system is by means of dispatching rules. The drawback of this method is that the performance of these rules depends on the state the system is in at each moment, and no one rule exists that overrules the rest in all the possible states that the system may be in. It would therefore be interesting to use the most appropriate rule at each moment. To achieve this goal, a scheduling approach which uses machine learning is presented in this paper. The methodology proposed in this paper may be divided into five basic steps. Firstly, definition of the appropriate control attributes for identifying the relevant manufacturing patterns. In second place, creation of a set of training examples using different values of the control attributes. Subsequently, acquiring of heuristic rules by means of a machine learning program. Then, using of the previously calculated heuristic rules to select the most appropriate dispatching rules, and finally testing of the performance of the approach. The approach that we propose is applied to a flow shop system and to a classic job shop configuration. The results demonstrate that this approach produces an improvement in the performance of the system when compared to the traditional method of using dispatching rules.

UMP Builder: Capturing and Exchanging Manufacturing Models for Sustainability

2018 ◽  
Author(s):  
William Z. Bernstein ◽  
David Lechevalier ◽  
Don Libes
Keyword(s):  
Environmental Analysis ◽  
Environmental Sustainability ◽  
Manufacturing Process ◽  
Manufacturing Systems ◽  
Information Model ◽  
Process Models ◽  
Data Driven ◽  
Manufacturing Processes ◽  
Initial Layer ◽  
Early Use

Targeting the improvement of environmental analysis of manufacturing systems, ASTM 3012-16 provides guidelines for formally characterizing manufacturing processes. However, the difficulty that has arisen in the early use of the standard illustrates the need for intuitive tools for helping modeling experts to conform to the specified information model. In response, we present the Unit Manufacturing Process (UMP) Builder, a browser-based tool integrating symbolic mathematical and guided textual inputs, helping to consistently record and exchange manufacturing process models for environmental sustainability. The tool provides an initial layer of governance and verification with respect to the conformance to ASTM 3012-16. In this paper, we (1) detail the requirements with developing such a tool, (2) propose an improved schema to represent UMP models accommodating data-driven techniques, and (3) demonstrate the tool using a contributed model from an open challenge for modeling manufacturing processes.

scholarly journals A Literature Review of Energy Efficiency and Sustainability in Manufacturing Systems

2021 ◽  
Vol 11 (16) ◽  
pp. 7366
Author(s):  
Paolo Renna ◽  
Sergio Materi
Keyword(s):  
Energy Efficiency ◽  
Renewable Energy ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Job Shop ◽  
Flow Shop ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Future Directions ◽  
Change Mitigation

Climate change mitigation, the goal of reducing CO2 emissions, more stringent regulations and the increment in energy costs have pushed researchers to study energy efficiency and renewable energy sources. Manufacturing systems are large energy consumers and are thus responsible for huge greenhouse gas emissions; for these reasons, many studies have focused on this topic recently. This review aims to summarize the most important papers on energy efficiency and renewable energy sources in manufacturing systems published in the last fifteen years. The works are grouped together, considering the system typology, i.e., manufacturing system subclasses (single machine, flow shop, job shop, etc.) or the assembly line, the developed energy-saving policies and the implementation of the renewable energy sources in the studied contexts. A description of the main approaches used in the analyzed papers was discussed. The conclusion reports the main findings of the review and suggests future directions for the researchers in the integration of renewable energy in the manufacturing systems consumption models.

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