Roll-to-Roll Manufacturing System Modeling and Analysis by Stream of Variation Theory

Author(s):  
Huanyi Shui ◽  
Xiaoning Jin ◽  
Jun Ni

A multistage system that consists of multiple stages for sequential operations to finish products is widely employed in modern manufacturing systems. Due to the characteristics of multistage systems, the product quality not only depends on operations in current stage but is also affected by operations in upstream stages. Most existing studies use Stream of Variation models to analyze error propagation and interactions among multiple stages in discrete manufacturing systems such as machining shops and assembly systems. In this paper, a multistage model based on the “Stream of Variation” concept is developed to investigate the tension propagation in a flexible material roll-to-roll manufacturing system. This modeling method uses a physical model coupled with a data-driven model to correlate the roller operation performance and product quality characteristics. Torque equilibrium analysis and Hooke’s law are employed for physical model and the censored regression model is used to explore unknown structures/parameters. A web unwinding process demonstrates the feasibility and prediction performance of the proposed model. The result shows that the proposed multistage model can serve as a virtual metrology method to increase system visibility, enhance health management capability and eventually improve product quality.

2007 ◽  
Vol 2007 ◽  
pp. 1-24 ◽  
Author(s):  
Jingshan Li ◽  
Ningjian Huang

The flexible manufacturing system (FMS) has attracted substantial amount of research effort during the last twenty years. Most of the studies address the issues of flexibility, productivity, cost, and so forth. The impact of flexible lines on product quality is less studied. This paper intends to address this issue by applying a Markov model to evaluate quality performance of a flexible manufacturing system. Closed expressions to calculate good part probability are derived and discussions to maintain high product quality are carried out. An example of flexible fixture in machining system is provided to illustrate the applicability of the method. The results of this study suggest a possible approach to investigate the impact of flexibility on product quality and, finally, with extensions and enrichment of the model, may lead to provide production engineers and managers a better understanding of the quality implications and to summarize some general guidelines of operation management in flexible manufacturing systems.


2021 ◽  
Vol 13 (10) ◽  
pp. 5495
Author(s):  
Mihai Andronie ◽  
George Lăzăroiu ◽  
Roxana Ștefănescu ◽  
Cristian Uță ◽  
Irina Dijmărescu

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.


2019 ◽  
Vol 957 ◽  
pp. 195-202 ◽  
Author(s):  
Elizaveta Gromova

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.


10.6036/9917 ◽  
2021 ◽  
Vol 96 (5) ◽  
pp. 455-459
Author(s):  
MAHDI NADERI ◽  
ANTONIO FERNÁNDEZ ULLOA ◽  
JOSÉ ENRIQUE ARES GÓMEZ ◽  
GUSTAVO PELÁEZ LOURIDO

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


Author(s):  
Xi Vincent Wang ◽  
Lihui Wang

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.


2014 ◽  
Vol 556-562 ◽  
pp. 6034-6037
Author(s):  
Dong Man Yu ◽  
Zhi Hua Gao ◽  
Xiao Jing Li ◽  
Di Wang

Reconfigurable manufacturing system is essential for sustainable change, rapid response ability important characteristics, research, development and application of manufacturing system. The main architecture and major characteristics of reconfigurable manufacturing systems is explored. Normally, the quality of RMS can be evaluated by several factors. Firstly, the gross cost of production and reconstruction should be less. Secondly, The time of design and manufacture (ascent time) should be shorter. Thirdly, the utilization ratio of existed resource should reach to the utmost. Finally, the cargo stream planning in common space should keep in optimal condition. At last, The author give an example to shown the RMS, the hydraulic integrated package for a gearshift device in automobile, are mentioned to compare and analyze.


Author(s):  
Abdul Salam Khan ◽  
Khawer Naeem ◽  
Raza Ullah Khan

An abrupt change requires a robust and flexible response from a manufacturing system. Dedicated Manufacturing System (DMS) has been a long practiced taxonomy for mass production and minimum varieties. In contrast, Flexible Manufacturing System (FMS) has been introduced for responding to quantity as well as variety issues. This study considers both production taxonomics by using a multi objective model of cost and time. An Integer Linear Programming (ILP) formulation is presented and subsequently validated. The analysis procedure is administered in two phases. In the first phase, comparison of production cost and process time in DMS and FMS is presented. The model is implemented by using an exact solution approach and results show that FMS is a viable option, compared to DMS, according to the criteria of cost, time, and productivity. In the second phase, sensitivity analysis is performed by using several FMS (n) and the impact of cells selection on the performance of system is studied. It is concluded that n=1 (single cell-based FMS) is more relevant for cost minimization; however, n = 6 is a suitable candidate for producing more quantity in given time horizon (process time minimization). Lastly, key findings are reported, and future research avenues are provided.


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