Introduction
Traditional and well-known manufacturing companies often struggle to implement newer process changes and manufacturing practices in business. Economic order quantity was a popular concept in the early part of 20th century. Almost all companies then used economic order quantity purchasing policy. Most of the companies probably benefitted from implementing economic order quantity (EOQ), but some failed as it was not relevant for the product type and industry. In the later part of 20th century, many new manufacturing process techniques came into limelight. Just in Time system, Toyota Production System, Theory of Constraints, MRP and ERP systems, TPM, Lean manufacturing and Lean Six Sigma are some of them. Many companies stated implementing those processes in the manufacturing system and substantially improved the overall function of the manufacturing and procurement process. However, many companies still failed after implementing the newer manufacturing techniques. Some companies were successful using only EOQ but many failed. This essay will discuss how economic order quantity (EOQ) philosophy holds up against just in time system, and how a traditional EOQ based manufacturing system can be improved using other manufacturing techniques like MRP and Theory of Constraints (TOC).
EOQ and Just in Time System for UK Manufacturing Company
EOQ was first introduced in 1915 by Ford W Harris. EOQ in simpler terms tries to balance the cost of ordering versus the cost of inventory holding (Zinn and Charnes 2005). If the total ordering quantity for a year is known, then a company may reduce the cost of ordering small quantities more frequently to minimize holding cost against the cost of ordering large batches to minimize ordering cost. EOQ is a scientific approach to arrive at an order quantity that optimizes the cost of holding and cost of ordering. Just in Time (JIT) System, on the other hand, is only concerned about the holding cost and tries to minimize the holding cost without disrupting the manufacturing process (Zinn and Charnes 2005). In fact, in a perfect just in time system, a company only holds inventory that is sufficient to cover for all production till the next material batch arrives. Just in time quantity is determined by multiplying daily demand with the time between two deliveries. It is, in fact, recommended that supplies should be as frequent as possible to reduce inventory and holding cost. However, just in time system totally ignores the ordering cost. EOQ in its calculation ignores the time between two deliveries as a variable. On the other hand, just in time ignores three EOQ variables like the cost of order, the products unit value and unit cost of inventory holding (Zinn and Charnes 2005).
Figure 1: EOQ and Cost (Deming 2014)
Economic order quantity uses more parameters to come to the final purchasing order quantity. From pure financial perspective, economic order quantity is a better process approach than JIT as it completely ignores the cost of ordering. In cases where the cost of holding is almost comparable with the cost of ordering, EOQ gives better results than JIT (Peavler 2014). For example, companies which procure sand for making glass probably should use EOQ to compute the procurement order quantity. Ordering small quantities of sand, sometimes, is not at all a good procurement practice. However, although the common knowledge says that EOQ is a better approach than JIT, we have seen more and more companies abandoning EOQ and going for JIT system. Is there anything which we have missed in our calculations?
Figure 2: Just in Time System using Kanban Containers (Toyota Motor Corporation 2014)
There are few factors beyond the scope of calculation but they impact the overall cost of the company. Firstly, economic order quantity tells us to order in large quantities than small batches. Large purchases means more space required for storing those items. Instead, if the company employs JIT technique, it will order small quantity and hence the storage space requirement will be less. In fact, if the company is paying rent for storage space, it can save money, if it follows JIT, by ordering small quantities (Peavler 2014). Also, in many cases for long vendor-manufacturer partnership, the cost of ordering small batches and the cost of ordering large batches do not vary much. In many cases, the unit cost of ordering almost remains same. In such cases, it is advisable to order small frequent batches than large batches. JIT makes more sense than EOQ. Furthermore, if a company orders a large quantity, then there is an inherent risk that the full inventory may not get used because the product which requires it may get changed before fully consuming the material (Peavler 2014). Then the rest of the material is fully wasted. Also, in some cases ordering large batches means the inventory is laying in the warehouse for a long time and because of multiple handling in the warehouse, the products may get damaged. In case of large orders, inventory sits in the warehouse for a long time occupying space. The company may not order other essential items and store it due to the lack of enough storage space. In such cases, there is huge ‘opportunity cost’ lost. These risk factors and opportunity costs are subjective and cannot always be calculated to see if JIT is better. However, depending on situations it can be judged which method is more suitable. For example, in computer chip making industry, if the company is holding too much stock of a particular type of raw material, it may end up not using that as the manufacturing process in computer industry is changing rapidly. In that industry, EOQ may not be a good practice (Peavler 2014). In fact, in that type of industry JIT is often the most used manufacturing process philosophy.
In case of our gearbox manufacturing company in concern, it is difficult to say that JIT is better than EOQ or vice versa. There are materials which are of low cost. For example, aluminium and magnesium are raw materials which are low cost compared to the ordering cost of other materials used in the gearbox manufacturing process. It makes absolute sense that those raw materials are procured in bulk quantities. As aluminium and magnesium are used in any model of gearboxes, even if the design and model of gearbox changes, the basic requirement of aluminium and magnesium will remain same. So it is unlikely to have huge demand fluctuation for magnesium and aluminium. It means that the company roughly knows what will be the yearly requirement for magnesium and aluminium. The cost of ordering and the cost of storing those raw materials are also known. Based on those figures, the UK based manufacturing company can decide the EOQ quantity of aluminium and magnesium. On the other hand, there are hundreds of other parts going into the production of gearbox. Many of the parts are directly procured from part manufacturers. These part manufacturers are based in USA. This means that the lead time for procuring such parts is high. Furthermore, it seems that ordering small quantities of parts may increase the cost of ordering substantially without much benefit to the manufacturer. As the lead time is high, the lead time uncertainty is also high and hence even ordering small quantities will stop the production process if the parts do not arrive on time. There are frequent changes to gearbox design, and thus many parts become obsolete after sometime. In such cases, JIT is the best practice but in case of the UK based gearbox manufacturing company, it will be difficult as the part vendors that supply parts to the main manufacturer are thousands of miles apart and the procurement lead time is very high.
EOQ and other manufacturing practices in the UK manufacturing Company
The management of the UK based gearbox manufacturing company is not convinced that it should discard the EOQ process it is following and implement JIT in its manufacturing system. We have seen in the previous section that although JIT is becoming more and more popular among all companies, but for this particular case JIT may not provide much benefit. It seems that the concerns of the management are true that implementing JIT will not provide much benefit to the current manufacturing process and that the investment in JIT will be a waste. In fact, JIT may cause production disruption. It seems that given the circumstances, it is better to take an approach to improve upon the existing EOQ methodology rather than implementing a completely new approach (JIT).
Joseph Orlicky in 1964 introduced the concept of MRP (Gershwin 2010). It was somewhat inspired by the Toyota Production System but was a slightly different approach towards material planning for production. Materials Requirement Planning (MRP) is an advanced approach over EOQ. Like EOQ, MRP tries to optimize between inventory level and ordering frequency. Apart from that, MRP also ensures that materials are available at the right time in right quantity for production and are also available for delivery to the customers (Gershwin 2010). MRP, apart from planning for availability of material and purchasing, also helps in the production scheduling and delivery scheduling. MRP helps in many ways. Firstly, MRP is the first process tool that provides a comprehensive end to end integrated manufacturing solution and procurement solution. It starts with the demand from the customers. Demand from the customers is known as the level ‘0’ bill of material (BOM) requirement. Based on this input, MRP creates two outputs. First it creates a production schedule which lays out the detailed production plan with routing and BOM requirements at each level of production. This is also known as the master production schedule (Gershwin 2010). Once the master production schedule is finalized, the raw materials and assembly part requirements are gathered based on the production quantities and BOM explosion. Based on the production schedule and purchasing ordering lot size techniques, (Like EOQ and lot-for-lot etc.) the final purchasing schedule is published (Gershwin 2010). Based on the above two outputs, production orders are published and sent to the production floor, and purchase orders are sent to the suppliers with quantity and date on which those are required. Like other systems, MRP also has some problems. First of all, in order for MRP to work perfectly, it is essential for the data MRP relies on to be correct. For example, MRP requires BOMs to calculate quantities of raw material and other part requirements to create a purchasing schedule. If the BOM is incorrect, then the whole process fails. Secondly, MRP provides a schedule which does not consider the capacity. It may so happen that the master production schedule provided by MRP is infeasible due to capacity constraints (Gershwin 2010). However, MRP II, an advanced version of MRP, takes care of most of the problems which are there in MRP.
Although MRP and MRP II provide a basic structure for production planning and procurement planning, it is not always feasible to consider the capacity of each and every resource to come up with a viable production schedule. The Theory of Constraints (TOC), which was introduced in 1984 by Goldratt in his book “The Goal”, talks about this problem at length. TOC assumes that all the parameters in a production facility can be measured in terms of throughput, operational excellence and inventory (Goldratt 2009). Throughput is the rate of money generation through sales. Inventory is the money invested in purchasing which the company intends to sell, and operational expense is the money a company spends to turn inventory into throughput. For most of the companies, the goal is to maximize the throughput (Goldratt 2009). TOC states that an organization first needs to identify the resources which are preventing it from increasing throughput directly and indirectly. Then the organization needs to decide how to exploit the constraints to maximize the throughput, given the system constraints. Finally, it needs to do a cost-benefit analysis to elevate the system constraint and compare it with an increase in throughput. For example, it was found by applying TOC that there is a machine preventing the increase of overall manufacturing process throughput. Then TOC states that the whole production planning and procurement planning should be centered on that resource (Goldratt 2009). Also, more research should be done to increase the capacity of the resource, which will increase the throughput.
In the case of the UK manufacturing plant, EOQ with MRP (or ERP) and TOC will definitely improve the overall manufacturing and procurement process. EOQ may continue to be used for determining procurement batch sizes with the help of MRP. However, TOC will be able to find out the resources with capacity constraints. MRP can produce production and procurement plan based on the capacity constraint. This can improve the availability of parts during production. This will optimize inventory, and the chances of inventory sitting for a long time in the warehouse will be reduced.
Conclusion
Economic order quantity is a very old purchasing policy. It is employed by many organizations and works very well for materials where the demand is stable, cost of the material is low and cost of storage is low. In such cases, it is advisable to procure materials in large batches to reduce the cost of ordering. In cases in which materials have a short shelf life or the demand of the product is not very stable, JIT is a better system than EOQ. However, even with unstable demand pattern sometime companies are forced to use EOQ and not JIT because of long lead times. In such cases, it is recommended for a company to develop its vendor base close to its production facility.
In cases where implementing JIT is not an option, there are other manufacturing and procurement techniques which can improve the overall process. MRP and TOC are two such processes which help in identifying the capacity constraint, create detailed production schedule according to customer demand, and produce a procurement plan to optimize the inventory cost and procurement cost. It is recommended for the UK based manufacturing company to implement MRP or an advanced version of MRP along with TOC, which will be the best way forward for them.
Works Cited
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