James C. Colson
IBM
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Robotics and Computer-integrated Manufacturing | 1985
James C. Colson; N. Duke Perreira
Abstract Most manufacturers of robotic systems have data sheets where a set of static performance measures are listed. To date, there has been no standardization on how these measures are obtained, what they mean, or what parameters are necessary in quantifying the performance of a robotic system. While some of the parameters currently specified lend themselves quite nicely to one class of systems, these same parameters are meaningless on other classes of systems. A generalized set of performance criteria, not biased towards any particular robotic system, is presented in this paper. Three groups of measures that can be used for quasi-static and dynamic performance analysis of any robot task are defined. These groups are accuracy, repeatability and resolution. For each group, there are a number of subclasses. For each subclass various sensitivities are presented. These include the effects of payload, approach direction and location in the work volume, or any other potential influence. A rather simplistic yet useful analogy of an archer is used to describe the terminology. The relationship of these measures to the ability to satisfactorily develop online and/or offline programs for a robotic system to perform an operation is described. A generic robotic system is presented, the sources of poor performance are identified and some of the more practical techniques to improve the performance of robotic systems are noted. A description of what should be measured and a generalized statistical technique for reducing that data so that all pertinent information is saved while the amount of actual data required is minimized is presented. A concise outline of the experimental procedures used to obtain unbiased robot performance data for determining the various aspects of a robotic systems performance and various forms of summarized performance tabulations are given. These tables of performance information would be beneficial to the quality control of manufacturing robots, for the product design engineer intending to use robots in manufacturing a product (design for manufacturing) and for the manufacturing engineer evaluating the purchase of various robotic systems.
IEEE Robotics & Automation Magazine | 1994
David C. Loose; James C. Colson
This paper outlines the development of a data-driven, fine pitch component placement machine, PPA-A, which is an integrated robotic workcell developed for attaching fine pitch integrated circuit components to printed circuit boards. In particular, the objectives for the machine are reviewed, and an overview of the solution is given. Problems encountered during the development are discussed, and details of the algorithms developed to solve these problems are given. These problems relate to achieving very precise placement of components, and are solved by novel calibration and execution schemes.<<ETX>>
Archive | 1998
Neal J. Alewine; James C. Colson; Abraham Ittycheriah; Stephane Herman Maes; Paul Andrew Moskowitz
Archive | 1999
James C. Colson; Neal J. Alewine
Archive | 1999
Neal J. Alewine; James C. Colson; David C. Loose; Sandeep K. Singhal
Archive | 1999
Stephen Glen Graham; Brent A. Miller; Steven M. Miller; Brian L. White Eagle; James C. Colson
Archive | 2003
James C. Colson; Brian L. White Eagle
Archive | 1998
James C. Colson; Stephen Glen Graham
Archive | 2000
James C. Colson; Brian L. White Eagle
Archive | 2000
James C. Colson; Sandeep K. Singhal