CONCEPTUAL MODEL OF THE PHYSICAL STRUCTURE OF MANUFACTURING SYSTEMS

2006 ◽  
Vol 16 (04) ◽  
pp. 643-651
Author(s):  
MYRIAM NOUREDDINE
Keyword(s):  
Conceptual Model ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Logical Structure ◽  
Physical Structure ◽  
Second Step ◽  
Abstraction Level ◽  
System A ◽  
Simple Format ◽  
High Abstraction Level

This paper deals with the generation of a conceptual model of the physical structure of any manufacturing system. The obtained conceptual model shows a clear and linear view of a given manufacturing system. A generic notation is used to guarantee the scalability and the portability of the model. This model maintains a high abstraction level without ambiguity and in a simple format. The generation of a conceptual model for a given manufacturing system is obtained through two steps. The first step describes both the physical structure and the logical structure of the manufacturing system. The second step gives the generation principle of the conceptual model. The approach is illustrated using an example.

Resilience Measures of Manufacturing Systems Under Disruptions

2014 ◽  
Author(s):  
Xi Gu ◽  
Xiaoning Jin ◽  
Jun Ni
Keyword(s):  
Manufacturing Systems ◽  
Manufacturing System ◽  
Production Condition ◽  
Unreliable Machines ◽  
System A ◽  
Multi Stage ◽  
Stage System ◽  
Normal Production ◽  
System Resilience ◽  
Production Losses

Unexpected disruptive events always interrupt normal production condition and cause production losses in the manufacturing system. A resilient system is capable of settling itself to the steady-state quickly after the disruption, and compensating for the lost production by using a relatively little overtime. In this paper, we define throughput settling time (TST) and overtime to recover (OTTR) as two resilience measures to analyze multi-stage serial-parallel systems with unreliable machines and finite intermediate buffers. We perform an exact analysis for a two-stage system and develop an approximation method for general multi-stage systems. Numerical case studies are conducted to investigate the system resilience under different configurations.

Mission Reliability Modeling of Manufacturing Processes and System

2012 ◽  
Vol 248 ◽  
pp. 450-455 ◽  
Author(s):  
Yan Chao Liu ◽  
Wen Jun Zhang ◽  
Gui Cui Fu ◽  
Nan Li
Keyword(s):  
Manufacturing Systems ◽  
Manufacturing System ◽  
Quality Parameters ◽  
Reliability Modeling ◽  
Inspection Errors ◽  
System A ◽  
Modeling Process ◽  
Discrete Manufacturing System ◽  
Two Factors ◽  
Quality Of Products

Mission reliability model is important for evaluation of the production capability of a manufacturing system. The manufacturing system mission reliability refers to the ability that the manufacturing system completes the production mission under specified conditions and within the specified time. The production mission includes two factors: quality of products and the productivity. Calculation of traditional evaluation parameters like Cpk and Ppk excludes the abnormal interruption of production and inspection errors. For some manufacturing systems with low degree of automation in the field of domestic weapons, both production disruptions and misjudgments in inspection processes have an impact on the mission reliability of the manufacturing system. A method of mission reliability modeling of discrete manufacturing system is proposed in this paper. The manufacturing system is composed of several processes. Abnormal interruption of production, inspection errors and substandard quality parameters of the products are involved in the modeling of the process mission reliability. The sequential and concurrent relationship between the processes is also taken into account in the modeling process.

Digital Twin of manufacturing systems: a case study on increasing the efficiency of reconfiguration

2020 ◽  
Vol 68 (6) ◽  
pp. 435-444 ◽  
Author(s):  
Behrang Ashtari Talkhestani ◽  
Michael Weyrich
Keyword(s):  
Manufacturing Systems ◽  
Manufacturing System ◽  
Added Value ◽  
Future Research ◽  
System Availability ◽  
Qualitative And Quantitative ◽  
Digital Twin ◽  
System A ◽  
Set Up

AbstractThe added value of a Digital Twin for reconfiguring manufacturing systems promises an increase in system availability, a reduction in set-up and conversion times and enables the manufacturing of customer-specific products. To evaluate this claim, this paper selects an architecture of the Digital Twin and realizes it on the basis of an application scenario for a cyber-physical manufacturing system. A case study is used to test the reconfiguration of a manufacturing system by comparing two different methods, one without and one with use of the Digital Twin. In this paper, the process steps of both reconfigurations are described and discussed in detail and a qualitative and quantitative evaluation of the reconfiguration results is presented. Finally, this paper gives an outlook on future research on intelligent automation of manufacturing systems using the Digital Twin.

scholarly journals Sustainable, Smart, and Sensing Technologies for Cyber-Physical Manufacturing Systems: A Systematic Literature Review

2021 ◽  
Vol 13 (10) ◽  
pp. 5495
Author(s):  
Mihai Andronie ◽  
George Lăzăroiu ◽  
Roxana Ștefănescu ◽  
Cristian Uță ◽  
Irina Dijmărescu
Keyword(s):  
Decision Making ◽  
Internet Of Things ◽  
Literature Review ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Data Driven ◽  
Smart Manufacturing ◽  
Production Networks ◽  
Production Logistics ◽  
Time Production

With growing evidence of the operational performance of cyber-physical manufacturing systems, there is a pivotal need for comprehending sustainable, smart, and sensing technologies underpinning data-driven decision-making processes. In this research, previous findings were cumulated showing that cyber-physical production networks operate automatically and smoothly with artificial intelligence-based decision-making algorithms in a sustainable manner and contribute to the literature by indicating that sustainable Internet of Things-based manufacturing systems function in an automated, robust, and flexible manner. Throughout October 2020 and April 2021, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “Internet of Things-based real-time production logistics”, “sustainable smart manufacturing”, “cyber-physical production system”, “industrial big data”, “sustainable organizational performance”, “cyber-physical smart manufacturing system”, and “sustainable Internet of Things-based manufacturing system”. As research published between 2018 and 2021 was inspected, and only 426 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, we selected 174 mainly empirical sources. Further developments should entail how cyber-physical production networks and Internet of Things-based real-time production logistics, by use of cognitive decision-making algorithms, enable the advancement of data-driven sustainable smart manufacturing.

Introduction of Flexible Manufacturing Systems as a Necessary Measure for the Russian Industrial Development

2019 ◽  
Vol 957 ◽  
pp. 195-202 ◽  
Author(s):  
Elizaveta Gromova
Keyword(s):  
Flexible Manufacturing ◽  
Flexible Manufacturing Systems ◽  
Industrial Development ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Agile Manufacturing ◽  
Industrial Sector ◽  
Business Environment ◽  
Maximum Speed ◽  
Industrial Enterprises

With the onset of the Fourth Industrial Revolution, the business environment becomes inherent in changes that occur with maximum speed, as well as characterized by the systemic nature of the consequences. One of them is the transformation of operational management models in industrial enterprises. The modern manufacturing system should focus not only on speed of response and flexibility, but also on the cost and quality of products. Integration of effective models: agile manufacturing, quick response manufacturing and lean production, in order to extract the best from them is proposed. The purpose of this study is to analyze this flexible manufacturing system and to relate it to the current state of the Russian industrial development. Theoretical and practical aspects of this model are presented. The examples of the flexible models introduction in the Russian industrial sector is allocated. The conclusion about the necessity of the flexible manufacturing systems implementation for the Russian industrial development is drawn.

DECISION SUPPORT FOR A SUSTAINABLE PRODUCTION IN JOB SHOP MANUFACTURING SYSTEMS

10.6036/9917 ◽  
2021 ◽  
Vol 96 (5) ◽  
pp. 455-459
Author(s):  
MAHDI NADERI ◽  
ANTONIO FERNÁNDEZ ULLOA ◽  
JOSÉ ENRIQUE ARES GÓMEZ ◽  
GUSTAVO PELÁEZ LOURIDO
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Job Shop ◽  
Sustainable Production ◽  
Ease Of Use ◽  
Manufacturing Companies ◽  
Strategic Decisions ◽  
Production Environments

Despite the growing importance that is being given to the concepts of sustainability in many areas, not only in industry but also in the economy and public opinion in general, until now, most research has focused, practically, on the analysis of the concepts, but has not addressed, in a comprehensive way, its impact in decision making probably due to the complex relations of interdependence between its different aspects. In this context, MAPSAM (Methodology for the Assessment of Sustainability in Manufacturing Processes and Systems) was created to help the decision-making process, allowing a conscious and transparent assessment by administrators and managers at the different levels of the structure of companies and organisations. This article explains its development and application in a "job shop" type manufacturing system with an approach that allows the integration of economic, environmental and social criteria. MAPSAM is based on the use of various techniques and tools to quantify the importance of each aspect of sustainability and it has been applied in other production environments, being implemented in different systems, analysing their ease of use and evaluating their behaviour. The objective is to show how it helps to make operational, tactical and strategic decisions in the management on these type of manufacturing companies and, specifically, in this contribution we want to highlight its versatility and applicability, by validating it in a certain type of layout. With this new application, MAPSAM increases its possibilities as an innovative instrument that allows companies to make conscious and sustainable decisions in order to be more efficient, fair, supportive and respectful of the environment. Keywords: Manufacturing System, Simulation, Decision Support, Sustainable Production, Decision-Making

Interoperability in Cloud Manufacturing and Practice on Private Cloud Structure for SMEs

2017 ◽  
Author(s):  
Xi Vincent Wang ◽  
Lihui Wang
Keyword(s):  
Manufacturing Systems ◽  
Manufacturing System ◽  
Research Work ◽  
Cloud Manufacturing ◽  
Cloud Services ◽  
Security Requirements ◽  
Research Trend ◽  
Safety Regulations ◽  
Multiple Challenges ◽  
New Research

In recent years, Cloud manufacturing has become a new research trend in manufacturing systems leading to the next generation of production paradigm. However, the interoperability issue still requires more research due to the heterogeneous environment caused by multiple Cloud services and applications developed in different platforms and languages. Therefore, this research aims to combat the interoperability issue in Cloud Manufacturing System. During implementation, the industrial users, especially Small- and Medium-sized Enterprises (SMEs), are normally short of budget for hardware and software investment due to financial stresses, but they are facing multiple challenges required by customers at the same time including security requirements, safety regulations. Therefore in this research work, the proposed Cloud manufacturing system is specifically tailored for SMEs.

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