PRODUCTION SYSTEMS ENGINEERING生产系统工程.pptVIP

* * * * * * * * * * * 2.2.1 Aggregation equations 11-* with initial conditions and boundary conditions 2.2.1 Aggregation equations (cont.) 11-* Convergence Theorem: The aggregation procedure is convergent: In addition, 2.2.1 Aggregation equations (cont.) 11-* Interpretation of and i = 2,…, M – 1 2.2.2 Formulas for performance measures 11-* Throughput or use the formulas for two-machine lines with and . Work-in-process For , use the two-machine formulas with and . Blockages and starvations 2.2.3 PSE Toolbox 11-* 2.2.4 Effects of up- and downtime Remain the same as in synchronous lines. 11-* 2.2.5 Asymptotic properties → min{ciei} → 0 → cMeM – 11-* 2.2.5 Asymptotic properties (cont.) Illustration 11-* 2.2.5 Asymptotic properties (cont.) 11-* 2.2.6 Accuracy of the estimates Lower than that for synchronous lines. εTP is on the average within 5%. εWIP is on the average within 8%. εSTi and εBLi is on the average within 0.03. 11-* 3. Case Studies 3.1 Automotive ignition coil processing system To account for the closed nature of the line, e1 and Tdown, 1 have been modified to 0.9226 and 19.12, respectively. 11-* 3.1.1 Model validation 11-* 3.1.2 Effect of starvation by pallets Observation: No significant TP improvement if the closed line is unimpeding. 11-* 3.1.3 Effect of increased buffer capacity and m9-10 efficiency Observation: Substantial improvement (similar to that obtained using the Bernoulli description) 11-* 3.2 Crankshaft production line (evaluation of the initial description) 11-* 3.2.1 Layout 3.2.2 Structural model 11-* 3.2.3 Machine and buffer parameters 11-* 3.2.4 Performance and “what if” analysis Sensitivity to buffer capacity Sensitivity to Sta. 7 efficiency Observation: Although the initial design meets specification, Sta. 7’s performance should be given a particular attention in order to maintain the production goal. 11-* 4. Summary The performance measure