scholarly journals Multidomain Simulation Model for Analysis of Geometric Variation and Productivity in Multi-Stage Assembly Systems

2020 ◽  
Vol 10 (18) ◽  
pp. 6606
Author(s):  
Sergio Benavent Nácher ◽  
Pedro Rosado Castellano ◽  
Fernando Romero Subirón ◽  
José V. Abellán-Nebot
Keyword(s):  
Manufacturing Systems ◽  
Production Quality ◽  
Assembly Systems ◽  
New Era ◽  
Multistage Manufacturing ◽  
Multi Stage ◽  
Potential Applicability ◽  
Stream Of Variation ◽  
Manufacturing Environments ◽  
Geometric Variation

Nowadays, the new era of industry 4.0 is forcing manufacturers to develop models and methods for managing the geometric variation of a final product in complex manufacturing environments, such as multistage manufacturing systems. The stream of variation model has been successfully applied to manage product geometric variation in these systems, but there is a lack of research studying its application together with the material and order flow in the system. In this work, which is focused on the production quality paradigm in a model-based system engineering context, a digital prototype is proposed to integrate productivity and part quality based on the stream of variation analysis in multistage assembly systems. The prototype was modelled and simulated with OpenModelica tool exploiting the Modelica language capabilities for multidomain simulations and its synergy with SysML. A case study is presented to validate the potential applicability of the approach. The proposed model and the results show a promising potential for future developments aligned with the production quality paradigm.

Stream of Variation Modeling and Analysis of Serial-Parallel Multistage Manufacturing Systems

2004 ◽  
Vol 126 (3) ◽  
pp. 611-618 ◽  
Author(s):  
Qiang Huang ◽  
Jianjun Shi
Keyword(s):  
Manufacturing Systems ◽  
Model Complexity ◽  
Modeling And Analysis ◽  
Multistage Manufacturing ◽  
Reduction Techniques ◽  
Process Route ◽  
Variation Propagation ◽  
Space Modeling ◽  
Multiple Routes ◽  
Stream Of Variation

In a Serial-Parallel Multistage Manufacturing System (SP-MMS), identical work-stations are utilized at each stage to meet the productivity and line balance requirements. In such a system, parts could go through different process routes and some routes may merge at certain stage(s). Due to the existence of multiple variation streams, it is challenging to model and analyze variation propagation in a system. This paper extends the state space modeling approach from single process route to the SP-MMS with multiple routes. Several model dimension reduction techniques are proposed to reduce model complexity. Properties of these techniques are studied from the perspectives of system representation and diagnosability. Furthermore, these techniques are applied to analyze system measurement strategies.

Simulation Optimization for Computer Models With Multivariate Output

2017 ◽  
Author(s):  
Raed Kontar ◽  
Shiyu Zhou ◽  
John Horst
Keyword(s):  
Gaussian Process ◽  
Manufacturing Systems ◽  
Performance Metrics ◽  
Simulation Optimization ◽  
Process Models ◽  
Manufacturing Performance ◽  
Gaussian Process Models ◽  
Multivariate Gaussian ◽  
Potential Applicability ◽  
Multivariate Gaussian Process

This paper explores the potential of Gaussian process based Metamodels for simulation optimization with multivariate outputs. Specifically we focus on Multivariate Gaussian process models established through separable and non-separable covariance structures. We discuss the advantages and drawbacks of each approach and their potential applicability in manufacturing systems. The advantageous features of the Multivariate Gaussian process models are then demonstrated in a case study for the optimization of manufacturing performance metrics.

Process-Oriented Tolerance Synthesis for Multistage Manufacturing Systems

2000 ◽  
Author(s):  
Yu Ding ◽  
Jionghua Jin ◽  
Dariusz Ceglarek ◽  
Jianjun Shi
Keyword(s):  
Product Design ◽  
Process Design ◽  
Manufacturing Systems ◽  
Minimum Cost ◽  
Manufacturing Processes ◽  
Industrial Case Study ◽  
Multistage Manufacturing ◽  
Process Oriented ◽  
Design Characteristics

Abstract In multistage manufacturing systems, quality of final products is strongly affected not only by product design characteristics but also by key process design characteristics. However, historically, tolerance research has primarily focused on allocating tolerances based on product design characteristics for each component. Currently, there is no analytical approach for multistage manufacturing processes to optimally allocate tolerances to integrate product and process characteristics at minimum cost. One of the major obstacles is that the relationship between tolerances of process and product characteristics is not well understood and modeled. Under this motivation, this paper aims at presenting a framework addressing the process-oriented (rather than product-oriented) tolerancing technique for multistage manufacturing processes. Based on a developed state space model, tolerances of process design characteristics at each fabrication stage are related to the quality of final product. All key elements in the framework are described and then derived for a multistage assembly process. An industrial case study is used to illustrate the proposed approach.

Mean Sojourn Time in Multi Stage Fork-Join Network

2015 ◽  
Vol 6 (3) ◽  
pp. 80-99 ◽  
Author(s):  
Yonit Barron
Keyword(s):  
Supply Chains ◽  
Sojourn Time ◽  
Computer Processing ◽  
Single Stage ◽  
Assembly Systems ◽  
Parallel Tasks ◽  
Multi Stage ◽  
Stage System ◽  
Major Factors ◽  
Performance Behavior

Fork-Join queue networks (F-J) have received increasing attention during the last Decade, due to their ability to model parallel and distributed computer processing, supply chains and assembly systems. However, most research is focused on a single stage processing, and only scant work exists on F-J with two or more stages. In this paper, the author investigates (through simulation) the performance behavior of a multi-stage system; in particular, the performance of a synchronized system is compared to an unsynchronized system regarding three major factors: (1) the number of parallel tasks; (2) the number of serial stages and (3) the utilization.

Demand Forecasting in Hybrid MTS/MTO Production Systems

2018 ◽  
Vol 5 (1) ◽  
pp. 63-78
Author(s):  
Moeen Sammak Jalali ◽  
S.M.T. Fatemi Ghomi
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Manufacturing Systems ◽  
Production Efficiency ◽  
Production Systems ◽  
Demand Forecasting ◽  
Series Analysis ◽  
Effective Decision ◽  
Effective Decision Making ◽  
Manufacturing Environments

This article describes how simplifying production-planning approaches for demand responsiveness has been well recognized as an operative means of accomplishing production efficiency. To support an effective decision making in manufacturing environments, this study will focus on adopting time series analysis concepts. It will attempt to focus on bringing forward novel structures for classifications of available surveying materials, which helps companies using time series analysis within production strategies to make a logical prediction of demands in hybrid manufacturing systems. In this regard, the authors will present two different categorizing structures as efficient ways of helping practitioners and academicians to find new approaches for applying near possible future forecasts by means of time series analysis methods.

Stream of Variation Based Error Compensation Strategy in Multi-Stage Manufacturing Processes

2005 ◽  
Author(s):  
Dragan Djurdjanovic ◽  
Jie Zhu
Keyword(s):  
Control Theory ◽  
State Space ◽  
Error Compensation ◽  
Manufacturing Systems ◽  
Tolerance Allocation ◽  
Measurement Technology ◽  
Natural Connection ◽  
Manufacturing Errors ◽  
Stream Of Variation ◽  
Linear State

Linear state space Stream of Variation (SoV) models of error flow in multistation assembly and machining systems have been well studied in the past decade. SoV models were utilized for identification of process-level root causes of manufacturing errors, quantitative characterization of measurements in multistation manufacturing systems, systematic selection of measurement points and features, as well as tolerance allocation and process design. Nevertheless, natural connection of the linear state space form of SoV models with traditional control theory has not been utilized to automatically compensate observed manufacturing errors and thus close the quality control loop. Recent advances in measurement technology and flexible fixtures make such operations possible and in this paper, we propose a method for strategic elimination of root causes of quality problems based on the SoV models of the flow of manufacturing errors. Furthermore, the concept of compensability that quantitatively depicts the capacity of error compensation in a specific system is proposed. Based on this concept analogous to the controllability in the traditional control theory, compensable and non-compensable subspaces of dimensional errors are identified and quantitatively described. Theoretical results have been demonstrated using the SoV model of a real industrial process used for machining of automotive cylinder heads.

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