Stream of Variation Modeling and Analysis for Multistage Manufacturing Processes

Shi, Jianjun

doi:10.1201/9781420003901

Cited by 187 publications

(133 citation statements)

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“…In order to overcome this limitation, manufacturers have begun to investigate ways to simultaneously evaluate product designs and manufacturing processes in an attempt to eliminate downstream manufacturing problems and reduce ramp-up times. For this purpose, product design requires the application of process-oriented approaches through 3D manufacturing variation models to integrate product and manufacturing process information [2]. However, the application of 3D manufacturing variation models is nowadays limited, specially in multi-station machining processes (MMPs) where a large number of machining operations is conducted in different stations with different fixture devices.…”

Section: Introductionmentioning

confidence: 99%

Manufacturing variation models in multi-station machining systems

Abellán-Nebot

Romero

Mira

2012

Int J Adv Manuf Technol

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In product design and quality improvement fields, the development of reliable 3D machining variation models for multi-station machining processes is a key issue to estimate the resulting geometrical and dimensional quality of manufactured parts, generate robust process plans, eliminate downstream manufacturing problems and reduce ramp-up times. In the literature, two main 3D machining variation models have been studied: the Stream of Variation (SoV) model, oriented to product quality improvement (fault diagnosis, process planning evaluation and selection, etc.), and the Model of the Manufactured Part (MoMP), oriented to product and manufacturing design activities (manufacturing and product tolerance analysis and synthesis). This paper reviews the fundamentals of each model and describes step by step how to derive them using a simple case study. The paper analyzes both models and compares their main characteristics and applications. A discussion about the drawbacks and limitations of each model and some potential research lines in this field are also presented.

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Section: Introductionmentioning

confidence: 99%

Manufacturing variation models in multi-station machining systems

Abellán-Nebot

Romero

Mira

2012

Int J Adv Manuf Technol

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“…Stream-of-variation (SoV) [50,51], a method based on the state-space model that is utilized in control system, has been developed to systematically analyse the quality propagation in multi-stage manufacturing systems, in order to identify the root-cause and reduce the product variation. Monte Carlo simulation methods can also be used to analyze the product variation [52].…”

Section: Maintaining Product Quality By Utilizing Principlementioning

confidence: 99%

Reconfigurable manufacturing systems: Principles, design, and future trends

2017

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Reconfigurable manufacturing systems (RMSs), which possess the advantages of both dedicated serial lines and flexible manufacturing systems, were introduced in the mid-1990s to address the challenges initiated by globalization. The principal goal of an RMS is to enhance the responsiveness of manufacturing systems to unforeseen changes in product demand. RMSs are costeffective because they boost productivity, and increase the lifetime of the manufacturing system. Because of the many streams in which a product may be produced on an RMS, maintaining product precision in an RMS is a challenge. But the experience with RMS in the last 20 years indicates that product quality can be definitely maintained by inserting in-line inspection stations. In this paper, we formulate the design and operational principles for RMSs, and provide a state-of-the-art review of the design and operations methodologies of RMSs according to these principles. Finally, we propose future research directions, and deliberate on how recent intelligent manufacturing technologies may advance the design and operations of RMSs.

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“…The models here do not necessarily capture precise nominal system behaviour as in model-based approaches, but rather a general understanding of how the system works. Another important approach that has been extensively used for diagnosis in manufacturing systems is Stream of Variation (SoV) theory [7] which aims to integrate multivariate statistics with control theory and design knowledge to provide root cause diagnosis, mostly for dimensional quality variation problems in multi-stage automotive assembly systems [8] and multi-stage machining processes [7]. It is worth noting that SoV works under the assumption of process linearity, however in reality this ceases to exist as various assembly processes are in fact non-linear such as welding thermal deformation, compliant deformation and contact interaction [9].…”

Section: Introductionmentioning

confidence: 99%

A methodology for developing local smart diagnostic models using expert knowledge

Madsen

Søndberg-Jeppesen

Lohse

et al. 2015

2015 IEEE 13th International Conference on Industrial Informatics (INDIN)

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Abstract-This paper describes an innovative modular component-based modelling approach for diagnostics and condition-monitoring of manufacturing equipment. The approach is based on the use of object-oriented Bayesian networks, which supports a natural decomposition of a large and complex system into a set of less complex components. The methodology consists of six steps supporting the development process: Begin, Design, Implement, Test, Analyse, and Deploy. The process is iterative and the steps should be repeated until a satisfactory model has been achieved. The paper describes the details of the methodology as well as illustrates the use of the componentbased modelling approach on a linear axis used in manufacturing. This application demonstrates the power and flexibility of the approach for diagnostics and condition-monitoring and shows a significant potential of the approach for modular componentbased modelling in manufacturing and other domains.

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Stream of Variation Modeling and Analysis for Multistage Manufacturing Processes

Cited by 187 publications

References 0 publications

Manufacturing variation models in multi-station machining systems

Manufacturing variation models in multi-station machining systems

Reconfigurable manufacturing systems: Principles, design, and future trends

A methodology for developing local smart diagnostic models using expert knowledge

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