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9. It is important to validate that the KANBAN loop prescribed converges with management's inventory turns objectives. In our example, there will typically be an average inventory of 6 KANBANs for each item.
During the work center's monthly operation, 212 hours of production, 53,000 parts will be produced (212*250 items per hour), the equivalent of some 241 KANBANs. These represent 20 different items each with about 6 KANBANs in average inventory, totaling 120 skids. This includes rolling stock as well as safety stock. Dividing 120 into 241 yields two turns per month, or 24 per annum. If this is not the magical number you are looking for, modify any one of the constraint or demand factors used in the calculation to change this result For instance, adjusting net capacity slightly, or reducing setup times even just a bit typically has a big impact on inventory turns. More capacity can also be assigned to the work center. Alternative work centers can also be assigned to some of the items. Demand can also be managed. We usually find that the inventory turn possibilities offered by this approach surprise many managers. They never realized simply optimizing stocks with the real constraints could do so much.

Let's discuss the EOQ once again. Recall that we mentioned that the EOQ should only be calculated using variable costs, and that these vary according to the time horizon considered. Management policy about inventory turns should be related to the costs over a three to twelve month medium term horizon, over which time at least the labor component is variable. The KANBAN calculation should focus on immediate to short term; which assumes labor is fixed, and thus setups are available at no extra cost if the capacity is available. If the inventory turns predicted by the KANBAN calculation exceeds the EOQ-based turns projected for the medium term horizon, this implies there is too much capacity on the shop floor. The contrary is also true. This is probably the only way to validate short term capacity, because it is the only approach that integrates mix, capacity, process vari­ability and demand constraints to deliver an inte­grated and optimized game plan. This breakthrough approach actively compensates for the weaknesses of MRP, the traditional KANBAN, and the Theory of Constraints by integrating them all together.

Implementing the Loops

10. As they say, the proof of the pudding is in the eating. Aside from when the KANBAN loops are being imple­mented the first time, the above calculation will be made regularly to allow the operators on the shop floor to modify, or at least anticipate the need to modify, existing KANBAN loops.

In the implementation phase, ensure each skid in process or in inventory contains the number of parts indicated by the KANBAN, and stick a KANBAN on each. Post remaining KANBANs on the KANBAN planning board at the respective supplier work cen­ters. If there are not enough KANBANs to go around, this indicates surplus inventory which will have to be slimmed down; do not add more KANBANs.
These new loops provide the production personnel with information about forecasted volumes that they may not already perceive on the shop floor. Shipping may not have started pulling the mix forecasted (Shipping actually triggers production in the pull environment by shipping skids and returning the consumed KANBANs to the last operation, and so on).

By complementing the foresight wrought into our calculated KANBANs with the operational know-how of the shop floor personnel, we will obtain the best of both worlds and allow the operators to react proactively to changes in the product mix and volumes. This proactive ability is typically absent from traditional production departments as well as in shops who have implemented KANBANs without incorporating the integrative and predictive aspects of the 7th rule.
Thus, based on the experience of the operators, these new suggested KANBAN loops can be implemented progressively by adding or removing KANBANs from the existing loops as the new mix manifests itself. Notice that in saying this, we have redefined the nature of the partnership which should exist between the planning department and operations.

For example, if the current KANBAN loop for a given customer-supplier relationship for a specific part is comprised of 13 KANBANs and the new calculated loop suggests 15, as soon as the operator feels the need to add new KANBANs (because the new mix is manifest­ing pull signals in that sense), his judgment will be vindicated by the projection. If, on the other hand, the operator perceives the need to diminish the number of KANBANs, the fact that the new loop recommends an increase instead will allow the operator to realize the signals he is getting are contrary and that he should investigate a little further; possibly the dip he is seeing is due to a direct or an indirect customer temporary down time. We will have given the operator guidelines providing a global appraisal of his upcoming mix, not just a snap shot on one part's situation.

The operator can also provide feedback about the param­eters used in the loop calculations, especially when he considers the suggested loops consistently too large or too small. These refinements will allow us to provide him with more sensitive and viable information.

Whereas the planner becomes an information liaison with the operator to provide him with the big picture, the role of the operator is to refine the loops with his experience and more detailed visibility. In the next section, we will see how the operator can do this so as to minimize stocks and maximize efficiency while meeting the customer's needs head on. This is his new measurement of productivity.

To Be Continued

For balance of this article, click on the below link:

Lean Manufacturing Articles and go to Series 01


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