Intended learning outcomes: Identify the calculation of anticipation time in the stochastic case. Produce an overview on the three parts of the generic principle of the technique. Explain the critical ratio of an order. Describe rescheduling of orders in process according to current materials management status. Present an evaluation of the technique. Identify its limitations and typical areas of application.

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Mixed manufacturing or mixed production is concurrent make-to-stock production and make-to-order production, using a single set of plant and equipment.
Mixed-mode manufacturers are manufacturing companies with mixed production.

Mixed-mode manufacturers produce and sell standard products whereby stocks are carried at various levels of production, including the final product. Standard product manufacturing aims for maximum possible utilization of capacity (cost objective). At the same time, mixed-mode manufacturers also produce goods to customer order, often in one-of-a-kind produc­tion. Here, the manufacturer aims for the shortest possible lead times (delivery objective).

The main objective of mixed-mode manufacturers is on-time delivery. The on-time delivery of custo­mer production orders takes high priority. Stock replenishment orders must be fulfilled on time — as soon as stocks have been depleted. The volume of orders of both types of orders is about the same. Simple logistics would call for separation and segmentation of the produc­tion resources. However, the very strength of some medium-sized organi­zations lies in their flexible planning & control, which allows them to make use of one and the same production infrastructure. They manufacture a relatively wide range of products based on specialized competence in a relatively small number of production processes.

Planning strategy: Manufacturing firms with mixed production re­qui­re a flexible planning strategy. By observing the natural logics of production management as practiced in medium-sized mixed-mode manufactu­rers, the following generic principle could be derived. For convenience, it is called capacity-oriented materials management, or Corma.

Capacity-oriented materials management (Corma) is an operations management principle that enables organizations to play off work-in- process against limited capacity and short lead times for customer production orders. See [Schö95b].

Corma makes intelligent use of capacity that generally is fully utilized but available short term, which leads to balanced loading. This helps to reduce queuing and thus lead times. Essentially, stock replenishment orders are viewed as “filler” loadings, whenever such a capacity is looking for an order. Orders are released periodically, in “packages”, provi­ding for optimal order sequencing, which reduces setup times. Thus, shorter lead times in make-to-order production confront a higher level of work-in-process in make-to-stock production.

The generic principle consists of three parts:

1. A criterion for order release that releases stock replenishment orders earlier than needed. An early order release is consi­dered as soon as there is available capacity in other­wise well-utilized work centers.
2. A scheduling technique or scheduling algorithm that for such orders entails work-in-process rather than early stock replenishment. Still, orders will be completed on time. However, customer production orders can be delivered with a minimum lead time. The key is continual reassigning of order priorities by estimating order slack time by (re-)calculation of either the critical ratio or a suitable lead-time-stretching factor of all orders.
3. A mechanism that couples shop floor scheduling with materials management. This is done by continually rescheduling stock replenishment orders according to the actual usage. The current physical inventory is converted into an appropriate latest completion date for the open replenishment order.

Thus, the Corma principle not only serves to release orders but also supports overall short-term planning & control from the order release to the moment when the goods either enter stock or are shipped to the customer. Long-term planning for goods and capacity is carried out independently of this. It can be based on traditional forecasting techniques: based on historical data for production with frequent repetition, or based on future projections for one-of-a-kind manufacture, for example.

Technique: In general, the generic principle is implemented manually. To do this, the planner uses a set of known planning and control techniques. Each of these techniques can (but does not need to) be supported by functions of conventional PPC software, or simply by personal implementation using Microsoft Excel or similar software. The following describes the techniques of the three parts of Corma in greater detail.

Corma, Part 1: Criterion for early order release. The planner regularly checks the loading of generally well-utilized capacity. As soon as short-term unused capacity is discovered, he checks on the availability of the products manufactured using this capacity. A work center where-used list can provide essential information for this first step. It is as if capacity is on the lookout for an order (hence, the term capacity-oriented materials management). If an “agent” is assigned to each capacity, agent-based systems may also be applied here.

In practice, it often happens that a particular product family is manufactured in a group of just a few work-centers. If one of the work centers of this group — in particular the gateway work center that performs the first operation of a particular routing sequence — is not being utilized, quite often the others are not in use either. An early order release thus usually means that several operations can be performed in advance.

Which of the products thus identified are candidates for early order release? The planner finds the answer by calculating the anticipation time for each possible item.

The anticipation time for an item is the time that will probably elapse before a production or procurement order must be released.

Figure 11.3.2.2 provides a formula for determining the articles that are candidates for an early release in the deterministic case. It takes into consideration all known transactions in the near future.

Figure 15.1.3.1 shows a graphical represen­tation of anticipation time in the stochastic case. This is the time expected to elapse before inventory falls below its order point, assuming average usage for the near future.

Fig. 15.1.3.1       Anticipation time in the stochastic case.

Figure 15.1.3.2 shows the formula for calculating the anticipation time.

Fig. 15.1.3.2       Calculating anticipation time in the stochastic case.

If there is more than one candidate for early order release, the product having the shorter anticipation time gains priority. Clearly, software can aid the planner in efficient calculation and decision-making.

Corma, Part 2: Scheduling technique for control of operations. New customer orders continu­al­ly alter the workload. They also “hinder” the progress of stock replenishment orders, and vice versa. In this situation, the planner continually reassigns the priority of all orders in process by estimating order slack times. A rough-cut estimation of order slack time is the following critical ratio.

The critical ratio of an order is obtained by dividing the time left until the order due date by the standard lead time of work left on the order.

A ratio < 1.0 indicates that the order is behind schedule; a ratio > 1.0 indicates that the job is ahead of schedule. The lower the result, the higher the order urgency in sequencing the operations of the order compared to those of other orders. Generally, the critical ratios of the orders can be obtained by an inquiry of the order database. The planner transfers a resulting priority to the production order as soon as he considers the difference compared to the actual order priority to be significant. As a result, this technique either accelerates or slows down the orders. It gives priority to early-released orders only when needed.

A more detailed and accurate measure of order urgency is obtained by implementing probable schedulingfor shop floor control. Here, the key is the calculation of a suitable lead-time-stretching factor. See Section 13.3.6. This factor is a more accurate measure for the order slack time than the critical ratio of the order, as it is defined as a numerical factor by which only the nontechnical inter­operation times and the administrative times are multiplied. Since the technical process itself determines the duration of operations and the technical inter­operation time, we can only modify slack time by increasing or reducing either the nontechnical inter­operation times or the administrative times.

Corma, Part 3: Coupling shop floor control with materials management. To do this, the planner checks the inventory on an ongoing basis and calculates the point in time at which inventory will fall at zero, assuming average use. This point in time becomes the probable date on which the replenishment order should arrive in stock. Clearly, software can provide for easy calculation here. The planners (or software) transfer this date to become the latest completion date for the replenishment order as soon as they consider the difference to the actual latest completion date to be significant. The following situations may arise:

• The latest completion date will be pushed forward, if inventory stock is being depleted at a rate faster than the statistical average for the period up to the point of order release. Rescheduling then calculates a smaller lead-time-stretching factor. This results in higher priority, and the order is accelerated.
• The latest completion date is postponed if inventory stock is being depleted at a rate slower than the statistical average for the period up to the point of order release. Rescheduling generates a higher lead-time-stretching factor. This results in lower priority, and the order is slowed down.

To show the effects of the Corma principle, let us look at a stock replenishment order with three production operations. Figure 15.1.3.3 shows four possible situations.

Fig. 15.1.3.3       Rescheduling of orders in process according to current materials management status.

• First situation: Because of the early order release, all three work opera­tions are evenly distributed between the earliest start date (i.e., the earliest possible start date of the order, which is originally the date of the early release and then moves — in fact — forward along the time axis with the “today” date) and the latest (acceptable) completion date for the order (that is, the order due date). They are all scheduled, but — in this situation — without priority. As a result, they are performed as soon as there are no more urgent operations waiting to be processed at the work station.
• Second situation: The mixed-mode manufacturer accepts an unplanned customer order with a high priority. Then the stock replenishment order in process will wait. Not even the first operation is performed. However, the ongoing rescheduling “discovers” any order that has waited for too long, and the latest start date, that is, “today,” is being pushed closer to the latest completion date. Rescheduling then calculates a smaller lead-time-stretching factor. This gives the order higher priority.
• Third situation: The inventory stocks fall faster than expected. The latest completion date is therefore brought forward. Rescheduling calculates a smaller lead-time-stretching factor, and the order is accelerated by expediting.[note 1506]
• Fourth situation: The inventory stocks fall slower than expected. Thus, the latest completion date is postponed. Rescheduling calcu­lates a higher lead-time-stretching factor, and the order is delayed.

The third and fourth situations in Figure 15.1.3.3 illustrate the most important aspect of the third part of Corma. Stock replenishment orders will receive the same priority as customer production orders if stock falls below safety stock. If the demand is lower than expected, however, stock replenishment orders will not even start, or will be halted. Alterations in the due date of a customer production order may also lead to resched­uling, with consequences similar to those in situations 3 and 4 above.

An example: Trox Hesco Corp. (Rüti, CH-8630, Switzerland). Trox Hesco (200 employees) develops, produces, and distributes ventilation products, such as air diffusion lattices and fire dampers. Trox Hesco manufacturing is based on high competency in a relatively small number of production processes. 500 different stock line items make up approximately 60% of sales volume. The same items, but made-to-order according to customer require­ments with respect to dimension, color, and so on, make up the other 40% of sales. Product structures and routings are of moderate complexity, with one to two production stages and about a dozen items in the bill of material and fewer than a dozen operations per stage.

As customer tolerance times are short, planning & control gives high priority to special cus­tomer orders. At the same time, however, stock replenishment orders must also be completed on time to prevent shortages. Stock replenishment orders can therefore compe­te with special customer orders. As demand for stock items is variable, the stock depletion date estimated at the moment of order release must now be verified. This allows determination of the priority of the replenishment order. While segmentation of the two production processes would make for simple logistics, this flexible planning & control of resources enables Trox Hesco to make use of the same production infrastructure for both modes of production.

Assessment of the technique and organizational considerations: Prerequisites for Corma:

• The increase in work-in-process, which results from the early release of stock replenishment orders, must be feasible economically and manageable in terms of volume. Corma does not result in premature inventory in stock, however.
• Early order release has to be possible to a sufficient degree. Orders that are released early are stock replenishment orders or customer production orders that start in advance of the latest start date.

There are some limitations involved in applying Corma:

• The focus has to be on a more balanced utilization of capacity, not maximal utilization. Load fluctuations will remain.
• Planners “on site” must be able to deal with constantly changing order inventories. They have to understand how to make the best use of the Corma recommendations, which may entail changing the sequence of operations that Corma proposes to accommodate additional, situation-specific information known to the planner.

Therefore, Corma is useful for the following areas of application:

• in addition to mixed production, in all cases where due dates must be met and, nonetheless, the system must be robust in the face of errors in planning dates or alterations in orders on hand;
• for self-regulating shop floor control (for mixed-mode manufacturers, for example), assuming that the data collected on order progress are precise enough. Because the basic premise of Corma is a constantly changing order backlog, it is robust enough to handle situational planning “on the spot,” which in this case is desirable;
• as a self-regulating system for short-term materials management. Owing to its conti­nuous coupling with materials management, an order may change its latest comple­tion date multiple times. A stock replenishment order may change its completion date up to the moment when inventories fall below the safety stock. From that moment onward, the replenishment order must be assigned to ongoing customer orders, since the replenishment order will serve to cover such customer orders. Since customer orders must have confirmed due dates that can no longer be changed, the replenishment order must also be given a fixed, or definitive, latest completion date.

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Course section 15.1: Subsections and their intended learning outcomes

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  15.1 Order Release

  Intended learning outcomes: Describe order proposals for production and procurement as well as order release. Explain load-oriented order release (Loor) and capacity-oriented materials management (Corma).

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  15.1.1 Order Proposals, Order Release for Procurement and Production, Accompanying Documents and Container Logistics

  Intended learning outcomes: Describe the reasons for order proposals for production or procurement. Differentiate between the dealing of order proposals for C items and of other items. Explain purchase order release. Explain production order release and describe the availability test of resources. Disclose issues linked with allocation and staging. Identify accompanying documents such as the traveling card and container logistics such as the two-bin inventory system.

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  15.1.2 Loor — Load-Oriented Order Release

  Intended learning outcomes: Produce an overview on the principle of the technique and the planning strategy. Describe the regulator analogy for load-oriented order release. Differentiate between time filter and load filter. Explain the steps of load-oriented order release. Present an evaluation of the technique. Identify its limitations and typical areas of application.

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  15.1.3 Corma — Capacity-Oriented Materials Management

  Intended learning outcomes: Identify the calculation of anticipation time in the stochastic case. Produce an overview on the three parts of the generic principle of the technique. Explain the critical ratio of an order. Describe rescheduling of orders in process according to current materials management status. Present an evaluation of the technique. Identify its limitations and typical areas of application.