valueflows

valueflows docs
git clone https://s.sonu.ch/~srfsh/valueflows.git
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commit 6d15a00485762a03d7eb8cfce995f1bde6f3e9ad
parent ddefa79003cae0627f29815942b16e4b12807c44
Author: Bob Haugen <bob.haugen@gmail.com>
Date:   Fri, 29 Mar 2019 08:35:59 -0500

fix typo
Diffstat:
Muse-cases/planning-scenario-time-based-resources.md | 2+-
1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/use-cases/planning-scenario-time-based-resources.md b/use-cases/planning-scenario-time-based-resources.md @@ -12,4 +12,4 @@ We have a friend who has been working on implementing a finite capacity planning It is possible to all three - MRP, CRP, and Finite Capacity Scheduling - using the same model, in the same system. ValueFlows will be able to support that. NRP was almost capable. I worked on [this skunkworks project](https://en.wikipedia.org/wiki/Quick_Response_Engine) in the mid-1990s that as capable of doing it all in real time, event-driven, always up-to-date. -If you look at that Finite Capacity Scheduling link, it lists a bewildering variety of complex techniques. We used a simple technique called production sequence synchronization, where the workloads for every time-based resource were sequenced according to the sequence of end-item demands. That way, each time-based resource will be scheduled for only one job at a time. We tried on optimization technique, but the manufacturing shop floor people hated it because it was very sensitive to any change in conditions and could reschedule everything if anything changed. Sequencing was not "optimal", but was good enough, and the sequences were stable unless an end-item demand changed. +If you look at that Finite Capacity Scheduling link, it lists a bewildering variety of complex techniques. We used a simple technique called production sequence synchronization, where the workloads for every time-based resource were sequenced according to the sequence of end-item demands. That way, each time-based resource will be scheduled for only one job at a time. We tried an optimization technique, but the manufacturing shop floor people hated it because it was very sensitive to any change in conditions and could reschedule everything if anything changed. Sequencing was not "optimal", but was good enough, and the sequences were stable unless an end-item demand changed.