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Enabling Autonomous Decision-Making in Manufacturing Systems through Preference Fusion

SAE International Journal of Materials and Manufacturing

Oakland University, USA-Slon Christopher, Pandey Vijitashwa
  • Journal Article
  • 05-13-02-0008
Published 2020-01-09 by SAE International in United States
Decision analysis (DA), a well-established discipline in business and engineering, is entering another domain of application due to the advent of Industry 4.0. DA enables optimal decisions by finding system parameters that maximize the utility, or in the presence of uncertainty the expected utility, from the attributes of a system. Whether there is a single decision maker or all decision makers have uniform preferences, determining risk behavior and the resulting utility is well developed in the existing literature. However, variability in preferences has not been satisfactorily addressed. This gap gains added significance in the face of the demands of Industry 4.0 where cyberphysical production systems must drive autonomous decision-making on the factory floor. The decisions must accommodate a distribution of customer and designer preferences, including production auditors within the organization. This article provides a novel framework and develops a closed-form approximation for expected utility in the presence of uncertainty in both attributes and preference behaviors. The value of this approach is demonstrated in the assembly of parts in a cyberphysical production system of an automotive…
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An Optimization Framework for Fixture Layout Design for Nonrigid Parts: An Automotive Perspective

SAE International Journal of Materials and Manufacturing

Oakland University, USA-Christopher Slon, Vijitashwa Pandey
  • Journal Article
  • 05-13-01-0001
Published 2019-11-19 by SAE International in United States
The inspection process of non-rigid parts during manufacturing and assembly is inherently challenging. This is exacerbated by the need for accurate real-time part data in the digital age. Although many ad hoc techniques exist, there are no rigorous methods to evaluate the quality of a fixture layout before final parts and gauges are available. This typically happens so late in the manufacturing process that errors found can scarcely be remedied. Additionally, the modifications to the gauge are usually costly and can result in significant delays, when performed this late in the process. This article proposes an optimization-driven mathematical approach tailored toward non-rigid parts to identify the best locator layout, early in the part design phase. A metric is proposed using robotic grasping theory to quantify the quality of the locating scheme and serves as the objective of optimization. The proposed method is implemented using a tolerancing software that performs finite element analysis (FEA) on the parts to predict its state given the force and torque inputs, including the effect of gravity. An evolutionary algorithm is…
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Mixture Distributions in Autonomous Decision-Making for Industry 4.0

SAE International Journal of Materials and Manufacturing

Oakland University, USA-Christopher Slon, Vijitashwa Pandey, Sam Kassoumeh
  • Journal Article
  • 05-12-02-0011
Published 2019-05-29 by SAE International in United States
Industry 4.0 is expected to revolutionize product development and, in particular, manufacturing systems. Cyber-physical production systems and digital twins of the product and process already provide the means to predict possible future states of the final product, given the current production parameters. With the advent of further data integration coupled with the need for autonomous decision-making, methods are needed to make decisions in real time and in an environment of uncertainty in both the possible outcomes and in the stakeholders’ preferences over them. This article proposes a method of autonomous decision-making in data-intensive environments, such as a cyber-physical assembly system. Theoretical results in group decision-making and utility maximization using mixture distributions are presented. This allows us to perform calculations on expected utility accurately and efficiently through closed-form expressions, which are also provided. The practical value of the method is illustrated with a door assembly example and compared to traditional random assembly methods and results.
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Straightening Technology Based on Displacement Control

Oakland University, USA-David Yang
Hefei University of Technology; P.R. China-Shouren Jiang, Xiaoxiang He
Published 2006-04-03 by SAE International in United States
Current mathematical model of straightening technology is based on the pressure control, which is difficult to apply to real production. A new mathematical model of straightening technology based on the displacement control is conducted. An equation involving the elastic zone ratio, the force parameter and the strain ratio relation is generated based on the influence of the elastic zone ratio during the precise straightening process. A further calculation methodology for straightening displacement is also introduced. This methodology is effective to the straightening parameter calculation on shafts and has been proven by experiments. It can also guide the precise straightening press design and manufacturing to some extend.
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