Discover hidden capacities in your Plant

Similarly, if you look at plants such as textiles/garment manufacturing, leather processing, where an order has multiple items and has to be delivered together (esp exports), you may not see a production skew but the order completion improves towards month-end. This leads to dispatch skew.

And the funny part is some of these companies claim very high on time delivery!

They don’t appear suddenly. Let me explain with an e.g. suppose a product requires 10 different components. Even if one component is missing the product cannot be completed. And the plant is manufacturing not one but different products and each product requiring multiple components. The different WCs in the plant are busy making components but whether that is helping in product completion, that is a question mark. What happens at month-end is expediting of missing components required for completing the product and that is why you would see better synchronization of components required for product completion.

But why this happens, just hold onto this for a moment. …………………..

Therefore, the practice of loading the plant more, increases the WIP and elongates production lead times. As the month progresses, the pressure of billing and customer follow-up/urgencies forces the plant to focus on order completion. This is the time when different components required for an order or product start coming together, resulting in production skew towards the month-end and poor on time performance.

Due to poor plant reliability and a production skew at month-end, Planner can make the next month’s plan only after month-end, considering back-log and next month orders. So by the time the next month plan is “frozen”, the plant undergoes starvation in the beginning of the month. This starvation along with urgencies (esp towards later part of the month) leads to loss of output and this in turn puts further pressure to load more. The plant is caught in a never-ending vicious loop of poor on time delivery, loss of output, higher order lead times and high inventories.

Even though intuitively the Plant knows that if they load with few orders they would get better on time delivery and lower lead times. But the fear of poor utilization, forces them to load more.

Every plant faces this conflict whether to load the plant with more orders (for better utilization) vis-a-vis loading with fewer order (for faster order completion). Companies try to resolve this conflict by monthly planning, but as explained earlier the lead time expands, lot of production happens towards month-end, on time performance goes for a toss and plant loses capacity. In a nutshell, the conflict remains unresolved. This conflict is at the root.

In most environments where touch time (i.e. just the machine process time & no waiting time), is less than 10% of total production lead time, visibility to the plant can be reduced by half. This means in a plant where production lead time is say about a month, the plant is allowed to work only on those orders which are due in the next 15 days instead of allowing all orders required in the entire month.

Since the choice set available at each WC is limited (around half from the earlier case), it prevents “cherry picking”/clubbing of future orders for bigger batches. This leads to faster order completion.

Now coming to the question if we allow few orders in the plant how will we prevent poor utilization of resources.

Way out is to deploy a solution with Push-Pull mechanism. Push mechanism is from planning perspective. Orders are scheduled chock-o’-block on the constraint resource (because CCR determines the output of the plant) based on its current capability. Approximate capacities are good enough. We don’t need a precise definition unlike APO (will explain that a bit later). Order due dates are determined based on the current pending load and not by overloading the plant.

The Pull mechanism is deployed in execution. Since CCR determines the output of the plant a certain WIP is maintained between the CCR & first WC, which is half of the current WIP (as explained earlier). The objective of this load/WIP is to not only prevent cherry picking but also starvation of CCR. So for some reason if this load drops below the desired level, more orders are released into the plant. Similarly if this load is going up due to lower output, further release of orders is stopped.

In a nutshell one is conservative in Planning by not overloading the plant but being aggressive in execution by pulling orders when the load goes down. By doing this the plant becomes highly reliable and the need for re-scheduling the plan goes away. One is able to achieve not only higher CCR utilization but also perfect de-coupling between Planning and Execution which was next to impossible in the previous scenario.

The entire endeavor is to ensure how orders complete in a faster time i.e. reduce production lead time and thereby, facilitating high on time delivery. For this we continuously collect data on where the orders are waiting for the highest time and then launch an improvement initiative to reduce this waiting time. For e.g. if the waiting queue is high before a particular WC, then the improvement project would explore how productivity can be improved so that the waiting time reduces.
For such improvement projects, Lean, six sigma techniques are used to improve productivity of that WC.
These initiatives are not taken once but continuously. Its called POOGI. It not only helps reduce lead time in the plant but also increases output of the system.