Use of Monte Carlo simulation to select dimensions, tolerances, and precision for automated assembly

Doydum, Cemal; Perreira, N. Duke

doi:10.1016/0278-6125(91)90034-y

Cited by 12 publications

(7 citation statements)

References 4 publications

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“…Tolerance modeling and analysis on the process side receive hardly any attention. In [34], the error model of the peg-in-hole assembly is set up for automated assembly, but it does not cover any errors before the insertion (placing) process. The relevant failure modes of automated assembly systems-involving precise grasping, releasing, and collision-are identified in [35]; however, only manufacturing errors and the robot repeatability are considered in the tolerances.…”

Section: Tolerance Modelingmentioning

confidence: 99%

Tolerance analysis for robotic pick-and-place operations

Tipary

Erdös

2021

Int J Adv Manuf Technol

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Robotic workcell design is a complex process, especially in case of flexible (e.g., bin-picking) workcells. The numerous requirements and the need for continuous system validation on multiple levels place a huge burden on the designers. There are a number of tools for analyzing the different aspects of robotic workcells, such as CAD software, system modelers, or grasp and path planners. However, the precision aspect of the robotic operation is often overlooked and tackled only as a matter of manipulator repeatability. This paper proposes a designer tool to assess the precision feasibility of robotic pick-and-place workcells from the operation point of view. This means that not only the manufacturing tolerances of the workpiece and the placing environment are considered, but the tolerance characteristics of the manipulation and metrology process (in case of flexible applications) as well. Correspondingly, the contribution of the paper is a novel tolerance modeling approach, where the tolerance stack-up is set up as a transformation chain of low-order kinematic pairs between the workpiece, manipulator, and other workcell components, based on manipulation, seizing, releasing, manufacturing, and metrology tolerances. Using this representation, the fulfillment of functional requirements (e.g., picking or placing precision) can be validated based on the tolerance range of corresponding chain members. By having a generalized underlying model, the proposed method covers generic industrial pick-and-place applications, including both conventional and flexible ones. The application of the method is presented in a semi-structured pick-and-place scenario.

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Section: Tolerance Modelingmentioning

confidence: 99%

Tolerance analysis for robotic pick-and-place operations

Tipary

Erdös

2021

Int J Adv Manuf Technol

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“…The cost equation, C M (t) = a + b/t 2 , as proposed by Spotts [10] has parameters a and b which can be estimated from regression based on dollar values. In addition to manufacturing costs occurring in-house, Taguchi suggests a loss function, 2 . This loss function represents the measurements of product quality characteristics, Y , deviating from the expected target, T , where K is the quality loss coefficient [11].…”

Section: Information Needed For Problem Optimizationmentioning

confidence: 99%

“…Authors who discuss this approach for assembly design include Doydum and Perreira, and Feng and Kusiak [2,3]. Doydum and Perreira propose the Monte Carlo Simulation as a design method for assemblies with irregular and complex cross sections.…”

Section: Introductionmentioning

confidence: 99%

Computer‐aided tolerance synthesis with statistical method and optimization techniques

Jeang

2001

Quality & Reliability Eng

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SUMMARYMost tolerance design optimization problems have focused on developing exact methods to reduce manufacturing cost or to increase product quality. The inherent assumption with this approach is that assembly functions are known before a tolerance design problem is analyzed. With the current development of CAD (Computer-Aided Design) software, design engineers can address the tolerance design problem without knowing assembly functions in advance. In this study, VSA-3D/Pro software, which contains a set of simulation tools, is employed to generate experimental assembly data. These computer experimental data will be converted into other forms such as total cost and Process Capability Index. Total cost consists of tolerance cost and quality loss. Then, empirical equations representing two variables can be obtained through a statistical regression method. After that, mathematical optimization and sensitivity analysis are performed within the constrained 'desired design and process' space. Consequently, tolerance design via computer experiments enables engineers to optimize design tolerance and manufacturing variation to achieve the highest quality at the most cost effective price during the design and planning stage.

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“…Regarding these aspects of product development, this study discusses an assembly design experiment which may be carried out via computer. Authors who discuss this approach for assembly design include Doydum and Perreira (1992) and Feng and Kusiak (1994). Doydum and Perreira propose the Monte Carlo simulation as a methodology for design of assemblies with irregular and complex cross sections.…”

Section: Introductionmentioning

confidence: 99%

Robust tolerance design by computer experiment

Jeang¹,

Leu²

1999

International Journal of Production Research

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Tolerance design a ects the quality and cost of a product cycle time. Most of the literature on tolerance design problems has focused on developing exact methods to minimize manufacturing cost or quality loss. The inherent assumption in this approach is that the assembly function is known before a tolerance design problem is analysed. With the current development in CAD (Computer-Aided Design) software, design engineers can proceed with the tolerance design problems, without knowing assembly functions in advance. In this study, the Monte Carlo simulation is employed using VSA-3D/Pro software to obtain experimental data. Then the design of experiments (DOE) approach is adopted for data analysis in order to select critical components for cost reduction and quality improvement. Implementing the discussed computer experiments, a tolerance design analysis which improves quality and reduces cost can be performed for any complex assembly via computer during the early stage of design.

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Use of Monte Carlo simulation to select dimensions, tolerances, and precision for automated assembly

Cited by 12 publications

References 4 publications

Tolerance analysis for robotic pick-and-place operations

Tolerance analysis for robotic pick-and-place operations

Computer‐aided tolerance synthesis with statistical method and optimization techniques

Robust tolerance design by computer experiment

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