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feedback [2021/01/17 01:55] 95.216.172.180 old revision restored (2020/11/27 00:48) |
feedback [2021/02/25 02:44] 167.114.159.183 old revision restored (2021/02/10 17:59) |
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- | ---- | + | RE: mbsetools.com / Index of / INTERNET SITE SOLUTIONS |

- | ====== Feedback ====== | + | This notification ENDS ON: Nov 08, 2020 |

- | Please, use this section to provide feedback. For example: | + | |

- | * A good solid effort for the first iteration. | ||

- | \\ | + | We have not received a payment from you. |

- | \\ | + | We've tried to email you however were unable to reach you. |

- | \\ | + | |

- | ---- | + | |

- | ====== TO-DO Task List ====== | + | |

- | ---- | ||

- | ===== General ===== | ||

- | * The helper function ' | ||

- | * Tim identified a good way to improve the SimWrapper_ functions (which enable a Simulink model to be called like a MATLAB function), but there' | ||

- | * Whether workstation models or inventory models, everything concerns a single-product system. | ||

- | * One idea to help this open-source effort grow: For a final project in graduate-level classes, require a meaningful contribution to the open-source project (a new analytical approximation, | ||

- | ---- | + | Please Go To: https://=mbsetools.com |

- | ===== Inventory Models ===== | + | |

- | * In the Base Stock and QR inventory simulation models, better ideas are needed for collection and visualization of backorder data; right now what's there is a bit of a hack. | + | For details as well as to make a discretionary settlement for services. |

- | * For the EOQ, Base Stock, and QR inventory simulation models, use regression to fit a multi-dimensional surface approximation (sometimes called a " | + | |

- | * Each system has a variety of things which can change (demand mean, scv, distrib type, cost parameters ...); make these the inputs. | + | |

- | * Each system has a variety of things which can be measured (costs, fill rate, inventory level ...); make these the outputs. | + | |

- | * If using multiple linear regression, then multiple outputs requires fitting multiple regression models, one per output. | + | |

- | ---- | + | Thank you. |

- | ===== Single Workstation Models ===== | + | |

- | * ALWAYS USE SCV, not variance. | + | 110820201053063454356 |

- | * The big three performance measures are Work-In-Process, | + | |

- | * The MM1, MMk, GG1, GGk analytical approximation functions are vectorized in either (1) arrival & processing time means & variances, or (2) number-of-servers K. However, the functions are not simultaneously vectorized in both sets of parameters, e.g. either one set or the other must be scalars. | + | |

- | * Hopp & Spearman in section 9.4.2 (ed. 2) derive analytical formulas for cycle time of a single workstation with process batching. | + | |

- | ---- | ||

- | ===== Production Line Models ===== | ||

- | |||

- | * Implement analytical formulas in Hopp & Spearman (ch. 7, ed. 2) for best-case, worst-case, and practical worst-case performance of a production line. The create experiements to test best-case, worst-case, and practical worst-case analytical results with simulation results. | ||

- | * Hopp & Spearman include equations 8.10-8.11 (ed. 2) to characterize the variability of a single workstation' | ||

- | |||

- | ==== Push Vs. Pull Dispatch Control ==== | ||

- | |||

- | * Implement analytical formulas in Hopp & Spearman (ch. 10, ed. 2) for analysis of CONWIP lines using mean-value analysis. | ||

- | * Tim observed that a true comparison of push versus pull would initialize the same blocks in side-by-side simulation models with the same random number seeds, e.g. use common random numbers. | ||

- | * Advanced: | ||

- | * Advanced: |

feedback.txt · Last modified: 2021/04/18 23:36 by 3.238.88.35