sc h e d u ling , before an d after lean M ark L . S pearman
The good news is that we have all the elements to create a generalised TPS that considers risk and randomness dynamic risk-based scheduling. The elements are:
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b. Instead of takt time production we apply the CONWIP release strategy. CONWIP naturally provides a smooth flow at the rate of the bottleneck as well as limiting WIP. This means that planned work orders become active work orders (WIP) only when the WIP level in the line falls below the maximum CONWIP level. WIP is calculated in terms of “equivalent WIP units” in order to account for routings with different lengths in a single flow.
Production planning is performed using traditional MRP to generate planned work orders with some important differences. Although MRP has a poor reputation, it does provide a hierarchical planning and scheduling system. Its deficiencies are addressed by periodically optimising the traditional parameters such as lot size, safety stock and planned lead time in ways that consider capacity, customer service, and inventory.
c. Recourse capacity is managed using a virtual queue and a capacity trigger. When planned work orders exceed a pre-determined maximum virtual queue level, the make-up time is authorised. This is done in such a way as to prevent late jobs without requiring a large capacity buffer at all times. In other words, instead of keeping an extra two hours for every 12 hour shift, we provide for a weekend shift for every week. Thus, if the weekend shift is not needed, it is not used.
a. Instead of insisting on a lot size of one, we compute optimal lot sizes that minimise inventory and out-of-pocket setup costs subject to capacity and service constraints. b. Instead of a fixed assignment of jobs to lines, we dynamically assign jobs to minimise the maximum utilisation of any machine in the system. This results in lower overall cycle times and less WIP.
If demand rises to the point where the system can no longer meet it, the virtual queue will increase to the point where the make-up time is needed. If this happens too often, the system will be re-optimised (shift schedules, workforce, lot size, etc.). If demand falls, the virtual queue will be empty indicating the need to reduce capacity. If there is no make-up time available (for example in a 24/7 schedule), then the only remaining buffer is time. Consequently, due dates will be pushed out to match what the system is capable of meeting. The use of dynamically quoted due dates is a key part of the dynamic risk-based scheduling strategy.
c. Rather than using heuristic inventory policies such as those used in kanban, we compute optimal levels of safety stock, days-of-supply, and planned lead times that require the minimum amount of inventory for the available capacity and desired customer service level. d. Instead of establishing a WIP level for every part at every work station as in kanban, WIP levels for an entire flow are optimised resulting in minimum WIP and cycle time while maintaining a given throughput.
The result is a system that: e. As opposed to the fixed lead times in traditional MRP systems, we periodically compute planned lead times based on anticipated load levels. Process centres with higher loads have longer lead times while those with low loads have much shorter lead times. The planned lead times include time spent in the virtual queue.
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Dynamic execution is performed without a published schedule. a. Planned work orders from the optimised MRP are not started on the “start date” (i.e., due date less planned lead time) unless allowed by the generalised pull system, CONWIP. Instead these are placed in a virtual queue awaiting the CONWIP pull signal. Thus, when demand drops, production goes down and when demand increases, production rises, within limits.
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Achieves the goals of the Toyota Production System in that it eliminates as much waste as is possible by minimising WIP, maximising throughput, maintaining on-time delivery and minimising inventory.
Eliminates the need to create detailed schedules of every job on every process during its time through the facility.
Works in a rich mix, low volume environment.
The system has been successfully implemented in a number of installations including one in textiles that managed more than 120,000 SKUs in which dye lot integrity must be maintained. The result has been lower inventory, better on-time delivery, and a higher utilisation of labor and equipment. It appears that the dynamic risk-based scheduling system can be applied to a much wider range of environments than the traditional Toyota Production System.