Kaizen: A Japanese term that means gradual, unending improvement by doing little things better and setting and achieving increasingly higher standards. Masaaki Imai made the term famous in his book, Kaizen: The Key to Japan’s Competitive Success.
Kanban: A method for providing material/product to a succeeding operation by signaling the preceding operation when more material/product is needed. This “pull” type of process control employs a kanban, a card or signboard, attached to a lot of material/product in a production line signifying the delivery of a given quantity. When all of the material/product has been processed, the card/sign is returned to its source, where it becomes an order to replenish.
New! Kano model: Three classes of customer requirements, as described by Noriaki Kano: satisfiers—what customers say they want; dissatisfiers—what customers expect and what results in dissatisfaction when not present; and delighters/exciters—new or unexpected features that customers do not expect.
Key performance indicator (KPI): A statistical measure of how well an organization is doing in a particular area. A KPI could measure an organization’s financial performance or how it is holding up against customer requirements.
Key process: A major system level process that supports the mission and satisfies major consumer requirements.
Key process characteristic: A process parameter that can affect safety or compliance with regulations, fit, function, performance or subsequent processing of product.
Key product characteristic: A product characteristic that can affect safety or compliance with regulations, fit, function, performance or subsequent processing of product.
Key results area: Customer requirements that are critical for the organization’s success.
Kitting: A process in which assemblers are supplied with kits—a box of parts, fittings and tools—for each task they perform. This eliminates time-consuming trips from one parts bin, tool crib or supply center to another to get necessary materials.
Kruskal-Wallis test: A nonparametric test to compare three or more samples. It tests the null hypothesis that all populations have identical distribution functions against the alternative hypothesis that at least one of the samples differs only with respect to location (median), if at all. It is the analogue to the F-test used in analysis of variance. While analysis of variance tests depend on the assumption that all populations under comparison are normally distributed, the Kruskal-Wallis test places no such restriction on the comparison. It is a logical extension of the Wilcoxon Mann-Whitney Test (see listing).