Manufacturing System Robustness Through Integrated Modeling

1999 ◽  
Vol 123 (4) ◽  
pp. 630-636 ◽  
Author(s):  
Rajiv Suri ◽  
Kevin Otto
Keyword(s):  
Robust Design ◽  
Manufacturing System ◽  
Parameter Design ◽  
Manufacturing Processes ◽  
Stretch Forming ◽  
Complete Set ◽  
Product Variation ◽  
System Robustness ◽  
Operating Points ◽  
Geographical Locations

Robust design techniques are often applied to the design of manufacturing processes to determine the most robust operating points for a production system. However, such efforts have traditionally been focused on treating the output of each manufacturing operation in isolation. This approach ignores the fact that the sensitivity of each operation to input variation is a function of the operating point, which can only be changed in conjunction with the operating points of all other operations in that system. As such, applying robust design to each operation within a system individually does not guarantee lowest end-of-line variation. This is contrary to commonly held beliefs. What is needed instead is a method for conducting a system-wide parameter design where the operating points of each operation are optimized as a complete set to reduce final product variation. The logistics of such an integrated parameter design scheme become difficult or impossible on processes that may occur in different geographical locations. In this paper we outline the use of mathematical models to conduct system-wide parameter design. We demonstrate this technique on a model of a sheet stretch-forming manufacturing system. Through this example, we show that selecting operating points while considering the entire system results in a greater reduction in variation than Taguchi-style robust design conducted independently on each of the operations within the system.

System-Level Robustness Through Integrated Modeling

1999 ◽  
Author(s):  
Rajiv Suri ◽  
Kevin Otto
Keyword(s):  
Manufacturing Systems ◽  
Integrated System ◽  
System Level ◽  
Parameter Design ◽  
Actual System ◽  
Variation Reduction ◽  
Reduction Strategies ◽  
Level Model ◽  
Product Variation ◽  
Operating Points

Abstract Variation reduction strategies have traditionally focused on treating the output of a single manufacturing operation. In practice, however, manufacturing systems are comprised of multiple operations, each of which can add to or reduce product variation. Additionally, the sensitivity of each operation to input variation is a function of the operating point, which can only be changed in conjunction with the operating points of all other operations in that system. As such, optimizing each operation within a system individually does not guarantee lowest end-of-line variation. What is needed instead is a method for conducting a system-level parameter design in which the operating points of each operation are optimized as a complete set to reduce final product variation. The logistics of such an integrated parameter design scheme make changes or designed experiments on the actual system unwieldy or impossible; instead a system level model can be used. In this paper we use Integrated System Models to conduct system-level parameter design. We demonstrate this technique on a model of a sheet stretch-forming manufacturing system. Through this example, we show that selecting operating points while considering the entire system results in a greater reduction in variation than Taguchi-style robust design conducted independently on each of the operations within the system.

Robust Tolerance Design for Quality

1996 ◽  
Vol 118 (1) ◽  
pp. 166-169 ◽  
Author(s):  
A. Kusiak ◽  
Chang-Xue Feng
Keyword(s):  
Design Of Experiments ◽  
System Design ◽  
Robust Design ◽  
Current Literature ◽  
Design Parameter ◽  
Parameter Design ◽  
Manufacturing Processes ◽  
Tolerance Design ◽  
Tolerance Synthesis

Design of a product (process) includes system design, parameter design, and tolerance design. Robust design is closely applicable to parameter design and tolerance design. The current literature on robust design has focused on parameter design while the problem of tolerance design has not been adequately covered. The tolerance design literature emphasizes the use of optimization to minimize cost while little attention has been paid to minimizing the sensitivity of tolerances to the variation of manufacturing processes. This paper discusses the application of the design of experiments (DOE) approach to tolerance synthesis to minimize manufacturing variations in a probabilistic case. The DOE approach is illustrated with an example.

An EDM Multi-Agent Collaborative Manufacturing System Based on Petri Net

2012 ◽  
Vol 457-458 ◽  
pp. 921-926
Author(s):  
Jin Zhi Zhao ◽  
Yuan Tao Liu ◽  
Hui Ying Zhao
Keyword(s):  
Petri Net ◽  
Manufacturing System ◽  
Intelligent Manufacturing ◽  
Agent Technology ◽  
Manufacturing Processes ◽  
Intelligent Manufacturing System ◽  
Collaborative Manufacturing ◽  
Model Based ◽  
Support Organizations ◽  
Multi Agent

A framework for building EDM collaborative manufacturing system using multi-agent technology to support organizations characterized by physically distributed, enterprise-wide, heterogeneous intelligent manufacturing system over Internet is proposed. According to the characteristics of agile EDM collaborative manufacturing system(AEDMCMS), the agent technology is combined with Petri net in order to analyze the model. Based on the basic Petri Net, the definition is extended and the Agent-oriented Petri net (APN) is proposed. AEDMCM is turned into the model of Petri Net which is suitable to the analysis and optimization of manufacturing processes.

Enabler für die personalisierte Produktion*/Automated additive manufacturing processes as enabler for personalized production – A sample application for tailor-made products

2019 ◽  
Vol 109 (03) ◽  
pp. 179-183
Author(s):  
J. Fischer ◽  
P. Springer ◽  
S. Fulga-Beising ◽  
K. Abu El-Qomsan
Keyword(s):  
Data Analysis ◽  
Additive Manufacturing ◽  
Manufacturing System ◽  
Personal Data ◽  
Industrie 4.0 ◽  
Manufacturing Processes ◽  
Automated Production ◽  
Sample Application

Das Fraunhofer IPA forscht an Workflows und Methoden für die Herstellung personalisierter Produkte von der Erfassung persönlicher Daten über die Analyse und Modellierung bis hin zur flexiblen, automatisierten Fertigung der Produkte. Der Beitrag beschreibt einen beispielhaften Anwendungsfall: die Herstellung einer personalisierten Brille. Für die nötige Flexibilität in der Fertigung wurde ein vollständig automatisiertes additives Fertigungssystem entwickelt, das im Applikationszentrum Industrie 4.0 des Fraunhofer IPA und des Instituts für Industrielle Fertigung und Fabrikbetrieb IFF der Universität Stuttgart integriert ist.   Fraunhofer IPA examines workflows and methods for the production of personalized products from the acquisition of personal data, analysis and modelling to the flexible, automated production of the products. This paper exemplifies an application using the production of personalized glasses. For this purpose, a fully automated additive manufacturing system was developed to provide the necessary flexibility in manufacturing.

scholarly journals Robust Design of a Multirotor Aerial Vehicle

2021 ◽  
Author(s):  
Abhishek Dutta
Keyword(s):  
Active Control ◽  
Conceptual Design ◽  
Robust Design ◽  
Physical System ◽  
Design Space ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
System Robustness ◽  
To Come

Abstract This paper introduces the methodology of systematic robust design of a multirotor vehicle as an example of how to carry out the robust design of a physical system. Robustness in aerial vehicles is highly desirable as it guarantees a desired level of performance even under environmental uncertainties. Thus far, robustness has been considered in terms of active control in the space of multirotor vehicles, but exploration of the design space itself is lacking. In this work, a conceptual design followed by a robust design is performed to come up with the specifications that lead to least uncertain performance of the multirotor vehicle with respect to stochastic wind disturbances.

Robust Concept Exploration of Materials, Products and Associated Manufacturing Processes

2018 ◽  
Author(s):  
Anand Balu Nellippallil ◽  
Pranav Mohan ◽  
Janet K. Allen ◽  
Farrokh Mistree
Keyword(s):  
Robust Design ◽  
Design Method ◽  
Integrated Design ◽  
Manufacturing Processes ◽  
Type I ◽  
Process Chain ◽  
Process Chains ◽  
Concept Exploration ◽  
Decision Based Design ◽  
Noise Factors

In this paper, we present robust concept exploration using a goal-oriented, inverse decision-based design method to carry out the integrated design of material, product and associated manufacturing processes by managing the uncertainty involved. The uncertainty in complex material and product systems is derived from many sources and we classify robust design based on these sources — uncertainty in noise factors (Type I robust design); uncertainty in design variables or control factors (Type II robust design); uncertainty in function relationship between control/noise and response (Type III robust design); and propagation and potential amplification of uncertainty in a process chain (Type I to III robust designs across process chains). In this paper, we introduce a variation to the existing goal-oriented inverse decision-based design method to bring in robustness for multiple conflicting goals from the stand-point of Type I to III robust design across process chains. The variation embodies the introduction of specific robust design goals and constraints anchored in the mathematical constructs of error margin indices and design capability indices to determine “satisficing robust design” specifications for given performance requirement ranges using the goal-oriented, inverse design method. The design of a hot rolling process chain for the production of a rod is used as an example.

Simulation of Manufacturing Processes via Virtual Reality

2018 ◽  
pp. 918-953
Author(s):  
Mohamed-Amine Abidi ◽  
Barbara Lyonnet ◽  
Pierre Chevaillier ◽  
Rosario Toscano ◽  
Patrick Baert
Keyword(s):  
Virtual Reality ◽  
Manufacturing System ◽  
State Of The Art ◽  
Simulation Method ◽  
Design Stage ◽  
Manufacturing Processes ◽  
Crucial Importance ◽  
Industrial Management ◽  
Technological Advances ◽  
Market Trends

In a world in continuous evolution, the different industrial actors need to be reactive to remain competitive and to conquer new market trends. To achieve this, they are constrained to improve their way of industrial management, both at the strategic level, to adapt to technological advances and follow market trends. In this chapter, we introduce a new simulation method that makes it easy to understand the results of a given simulation. This is of crucial importance because the design stage of a manufacturing system usually implies not specialist actors. The objective of the chapter is to present the main advantages of using the virtual reality (VR) to the manufacturing processes simulation. To this end, a state of the art will compose the first part of the chapter. In the second part, we address the issue of the contribution of the VR to the industrial simulation.

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