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In this paper, we suggest a potential use of data compression measures, such as the Entropy, and the Huffman Coding, to assess the effects of noise factors on the reliability of tested systems. In particular, we extend the Taguchi method for robust design by computing the entropy of the percent contribution values of the noise factors. The new measures are computed already at the parameter-design stage, and together with the traditional S/N ratios enable the specification of a robust design. Assuming that (some of) the noise factors should be naturalized, the entropy of a design reflects the potential efforts that will be required in the tolerance-design stage to reach a more reliable system. Using a small example, we illustrate the contribution of the new measure that might alter the designer decision in comparison with the traditional Taguchi method, and ultimately obtain a system with a lower quality loss. Assuming that the percent contribution values can reflect the probability of a noise factor to trigger a disturbance in the system response, a series of probabilistic algorithms can be applied to the robust design problem. We focus on the Huffman coding algorithm, and show how to implement this algorithm such that the designer obtains the minimal expected number of tests in order to find the disturbing noise factor. The entropy measure, in this case, provides the lower bound on the algorithm's performance. [ABSTRACT FROM AUTHOR]

;Remote learning has been an increasingly growing field in the last two decades. The Internet development, as well as the increase in PC's capabilities and bandwidth capacity, has made remote learning through the internet a convenient learning preference, leading to a variety of new interfaces and methods. In this work, we consider a remote learning interface, developed in a Computer Integrated Manufacturing (CIM) Laboratory, and evaluate the contribution of different interface components to the overall performance and learning ability of end users. The evaluated components are the control method of the robotic arm and the use of a three-dimensional simulation tool before and during the execution of a robotic task. An experiment is designed and executed, comparing alternative interface designs for remote learning of robotic operation. A teleoperation task was given to 120 engineering students through five semesters. The number of steps required for completing the task, the number of errors during the execution, and the improvement rate during the execution were measured and analyzed. The results provide guidelines for a better design of an interface for remote learning of robotic operation. The main contribution of this paper is in the introduction of a new teaching tool for laboratories and the supplied guidelines for an efficient design of such tools. [ABSTRACT FROM PUBLISHER]