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Lean manufacturing has greatly changed the way many companies produce products. Lessons learned in lean manufacturing are being applied to many non-manufacturing situations including design, logistics, and transactional processes. Such tools can be applied to metallurgical laboratories which support daily production or design and development. Four key principles of lean management and nine tools are presented with specific examples demonstrating how these lean tools can be successfully applied to a metallurgical laboratory operations. These principles and tools have been successfully implemented by the author in a captive metallurgical laboratory over the last year resulting in reduced cycle time, higher productivity, less variation in analysis methods allowing for direct comparison of data over time, and improved quality.

Process data curves are plots of process characteristics as a function of time over one cycle. Statistical analysis of these curves has not been feasible in the past due to lengthy calculations compounded by large data sets. This paper presents a statistical analysis method for process data curves using today's computers. This method involves collection of process data, descrete models creation, and the calculation of control limit curves. When plotting process data with control limit curves, variation can be identified and improvements can be made to the process. This technique of statistical process control can be applied to numerous process.

Many manufacturers utilize statistical methods to control product characteristics during processing. Often traditional x charts are utilized. This method is appropriate when examining characteristics with one degree of freedom. For features with two or more degrees of freedom, traditional x charts may be misleading. Techniques for controlling characteristics with multiple degrees of freedom, however, have not been developed. The purpose of this paper is to present a method of statistical analysis using radial type charting techniques for characteristics with multiple degrees of freedom. Included in this paper is a detailed discussion of the steps to prepare and interpret radial type charts. These techniques are applied to true position measurements as a specific example.