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There is more to just-in-time than its usual manufacturing-centered explication. Inasmuch as manufacturing ends with order-fulfillment to distributors, retailers, and end users, and also includes remanufacturing, repair, and warranty claims, just-in-time's concepts and methods have application downstream from manufacturing itself.
Tracing just-in-time compilation is a technique used by virtual machines to optimize the execution of a program at runtime. This is done by recording a linear sequence of frequently executed operations, compiling them to native machine code and executing them. This is opposed to traditional just-in-time (JIT) compilers that work on a per-method ...
Kanban (Japanese: 看板 meaning signboard) is a scheduling system for lean manufacturing (also called just-in-time manufacturing, abbreviated JIT). [2] Taiichi Ohno, an industrial engineer at Toyota, developed kanban to improve manufacturing efficiency. [3] The system takes its name from the cards that track production within a factory.
In computing, just-in-time (JIT) compilation (also dynamic translation or run-time compilations) [1] is compilation (of computer code) during execution of a program (at run time) rather than before execution. [2] This may consist of source code translation but is more commonly bytecode translation to machine code, which is then executed ...
Chapter 15 Just In Time - Phrase invented by Kiichiro Toyoda - the first president of Toyota. There is conflict on what the actual English translation of what "just in time" really means. Taiichi Ohno quoted from the book says " 'Just In Time' should be interpreted to mean that it is a problem when parts are delivered too early". [21]
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^NDX data by YCharts. If Buffett's analysis from over two decades ago is still on point, the stock market is again looking downright bubbly. Remember that he cautioned in 2001 that if the ratio ...
In time series analysis, the Box–Jenkins method, [1] named after the statisticians George Box and Gwilym Jenkins, applies autoregressive moving average (ARMA) or autoregressive integrated moving average (ARIMA) models to find the best fit of a time-series model to past values of a time series.