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A Decision Based Mobility Model for Semi and Fully Autonomous Vehicles

FCA US LLC-Christopher Slon
Oakland University-Vijitashwa Pandey, Line Deschenes
  • Technical Paper
  • 2020-01-0747
To be published on 2020-04-14 by SAE International in United States
With the emergence of intelligent ground vehicles, an objective evaluation of vehicle mobility has become an even more challenging task. Vehicle mobility refers to the ability of a ground vehicle to traverse from one point to another, preferably in an optimal way. Numerous techniques exist for evaluating the mobility of vehicles on paved roads, both quantitatively and qualitatively, however, capabilities to evaluate their off-road performance remains limited. Whereas a vehicle’s off-road mobility may be significantly enhanced with intelligence, it also introduces many new variables into the decision making process that must be considered. In this paper, we present a decision analytic framework to accomplish this task. In our approach, a vehicle’s mobility is modeled using an operator’s preferences over multiple mobility attributes of concern. We also provide a method to analyze various operating scenarios including the ability to mitigate uncertainty in the vehicles inputs. An example of this is the collection of soil properties data using techniques such as remote sensing. Operators of these vehicles are interested in finding the value of collecting such information.…
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Assessing Fit and Finish Design Sensitivity By Mapping Measurements to VNM Utility

FCA US LLC-Christopher Slon, Xiaona LI, Vita Valetchikov
Oakland University-Vijitashwa Pandey
  • Technical Paper
  • 2020-01-0600
To be published on 2020-04-14 by SAE International in United States
In the automotive industry “fit and finish” is the term applied to the perceived quality of the alignment of one part to another. Fit and finish gives the buyer a sense of the overall quality of the vehicle purely from an aesthetic perspective. Fit and finish is usually evaluated by the manufacturer through dimensional measurements of the “gap” and “flush” conditions between panels. Since variation in the measurements increases the probability that a vehicle will result in poor fit and finish, relatively arbitrary limits are put on these measurements to define whether a gap or flush condition is acceptable or not. It is suspected that the relationship between the appropriate measurement limits and the customer’s perception of quality is highly influenced by the design of the interface between panels. This paper proposes a method to evaluate the sensitivity of the perceived quality of the designed interface to variation in the measurements of gap and flush. The novelty is in the application of the concept of von Neumann-Morgestern utility to fit and finish. The significance is…
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Reconciling Simultaneous Evolution of Ground Vehicle Capabilities and Operator Preferences

FCA US LLC-Christopher Slon
Oakland University-Vijitashwa Pandey
  • Technical Paper
  • 2020-01-0172
To be published on 2020-04-14 by SAE International in United States
An objective evaluation of ground vehicle performance is a challenging task. This is further exacerbated by the increasing level of autonomy, dynamically changing the roles and capabilities of these vehicles. In the context of decision making involving these vehicles, as the capabilities of the vehicles improve, there is a concurrent change in the preferences of the decision makers operating the vehicles that must be accounted for. Decision based methods are a natural choice when multiple conflicting attributes are present, however, most of the literature focuses on static preferences. In this paper, we provide a sequential Bayesian framework to accommodate time varying preferences. The utility function is considered a stochastic function with the shape parameters themselves being random variables. In the proposed approach, initially the shape parameters model either uncertain preferences or variation in the preferences because of the presence of multiple decision makers. We consider this utility distribution as the prior and update it to a posterior with feedback acquired from actual system use. The framework improves the utility function and thereby the decisions made…
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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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