Case Study : Auto component Industry - Improving the Flow using Theory of Constraints Methodology

Case Study : Auto component Industry - Improving the Flow using Theory of Constraints Methodology

While everyone aspires to be a Tier 1 supplier in the Automobile Industry, it is observed that this industry is not only volatile with rather unreliable forecasts, but it is also an industry that generally ends up spending more time and money that is required on a daily basis in the process of expediting alone. Given the importance of a high performing, perfectly working supply chain and production management, companies approach us to rectify processes in order to improve productivity, sales and hence profits, while reducing costs. Explained here is the generalized solution to a commonly faced supply chain issue in the industry, with the help of one of the many case studies that we have performed.

The Problem.

The supply chain is characteristically designed as a straight-forward equation that relies largely on the suppliers adhering to the On-time and In-Full (OTIF) order fulfilment as per schedules. Standard tolerance percentages are measured and considered. Despite all the precautionary measures, a disjoint and a small degree of chaos are experienced in most supply chains. Of the reasons behind the manufacturing undulations, we have singled out the largest hindrance, and will explain the same via the example of our client, Aakar Foundry.

The biggest problem faced by the suppliers is the failure to comply to the OTIF despite being provided the schedule as ahead as three months in advance. Let us consider the case of Aakar Foundry. In this particular case of Aakar, the Raw Material (RM) procurement was planned well in advance and in accordance with the schedules provided. Despite the planning and the state-of-art manufacturing facility that had a much larger production capacity than the current requirement, Aakar failed to meet with the delivery demands in the stipulated time. 

The Standard Solution.

The standard procedure to deal with problems of this kind is to maintain high inventories of raw materials (RM), finished goods (FG), and works in progress (WIPs). This solution, however, falls short, owing to the following restrictions:

- Due to the prior lack of adherence to the delivery requirements, Aakar has been in non-negotiable terms rendering Aakar unable to procure a price increment from its clients. Without the additional budgets, it is not possible for Aakar to assign a larger amount of money that is tied in because of the additional inventory that it needs to maintain to deal with the problem of OTIF compliance.

- Along with the unavailability of additional funds, Aakar has to deal with fluctuations in the raw material costs. These fluctuations in the raw material costs further lead to fluctuations in the production and production costs.

- The customer demands and buying quantities change as well, owing to various factors within the market and that causes extreme fluctuations in the production planning.

THE BULLWHIP EFFECT

Here let us delve into an important term called the Bullwhip Effect or the Forrester Effect.

Bullwhip effect, the noteworthy supply chain phenomenon was first observed by the MIT Systems Scientist Jay Forrester. Hereon, the bullwhip effect became one of the most important factors that are taken into consideration in the supply chain management in most industries, more so the Automobile sector. At the cusp of the concept of the bullwhip effect is ‘waves’ of inventory fluctuations formed in the supply chain of suppliers in response to slight variations in the customer demands. This happens in the pursuit of adjusting the production forecasts in accordance with the demand variations with the intention of meeting the customer demands every time. The bullwhip effect is, hence, the outcome of the adjustments made by the supplier in his manufacturing and supply chain in response to the variations in demand as experienced by the customer. These ‘waves’ caused by slight demand fluctuations are so high that a change of about +/- five percent in the point-of-sale-demand will cause changes in demand of up to +/- forty percent for the supply chain participants. Obviously, the reason this is called the Bullwhip Effect is because the graph looks literally like a bullwhip. The causes of the Bullwhip Effect are found to be both operational as well as psychological. 

An innovative solution.

The perfect solution for the aforementioned problems is an elusive beast and the pursuit of all companies. It is, therefore, necessary to approach the problem outside the restrictions of the tradition bounds. The solution revolves around four major theories that are explained in order of occurrence.

A] Maintaining Stock Buffers

As the first part of the solution, the Tier 1 maintains FG buffer, RM buffer and WIP buffer. A company is to supply the daily requirement of OEMs from the FG buffer alone. In this aspect, production requires the process to fill in the FG buffer first with the help of the WIP buffer, then replenishing the WIP buffer from the RM buffer, meaning that instead of reacting directly to the varying schedules provided by the OEMs. This solution is by far the most effective in solving the problem of responsive production by shortening lead times. Although this solution can be perceived as a straight-forward one, it is a critical change to the supply chain functions wherein the stock levels are calculated based upon the replenishment lead times and daily demand, instead of the overall lead times and the unreliable OED schedules. This process change is beneficial to the Tier II suppliers just as it is ideal for the Tier I suppliers.

Challenges

Other than the most obvious challenges, there are a few that will stand out. Those are as follows:

1) The load on the plant being higher than its capacity on a given day. As is generally calculated, the load on a plant is the difference between the target level of the FG inventory and the current stock across all SKUs. 2) The capacity of the plant is subjected to reduce owing to numerous factors not associated with the machinery capacity of the manufacturing unit. These reasons include but are not limited to absenteeism, unavailability of manpower and machinery breakdowns.

Given that the objective remains to have higher levels of FG in the company warehouses ready to ship in order to reduce the lead time, the job priorities are decided based on the requirements of stock and the available buffer. 

B] Use of the Stock Keeping Unit, or SKU

As you are aware, the purpose of the SKU, or the Stock Keeping Unit is to track the inventory in the manufacturing process. Hence, the lower the stock is in comparison to the assigned SKU, the higher is the priority of that buffer. This process makes the tracking and processes for supply chain convenient and profitable. This process is standardized across the company and adhered to by every level of employees. The SKU levels are divided into three zones - Red, for the lowest permissible level, Yellow is acceptable level and Green is the target level. The stock levels are required to stay between these three levels. Obviously then, the stock that has gone to the red level of the SKU is given topmost priority followed by the stock that is in the yellow level and the stock that is at the green level has the lowest priority assigned to it.

C] Dynamic Buffer Management

Now, in each buffer, the stocks are divided into three zones and are colour coded as per the levels that are impending upon the SKU. This method is a part of the Dynamic Buffer Management. Dynamic Buffer Management is a tool from the larger Theory of Constraints. Given that the new competition is between suppliers and the new focus of business is the perfect alignment and synchronisation of the supply chain, the Dynamic Buffer Management Theory is given its due credit in the facilitation of the same. The daily reports of the buffer penetration (the stock that is used in relation to the SKU levels) are generated and as per the priority the stocks are replenished. The stock that is required to replenish the RM buffer for a Tier I supplier needs to be present in the FG buffer of the Tier II supplier for this system to work seamlessly. The stock that is in the red zone is given highest priority of manufacturing by the Tier II supplier to maintain the lead time required across the chain at the minimum. In this ecosystem, the Tier II supplier is expected to keep buffers of items similar to those in the buffers of Tier I suppliers and is provided assistance for the production planning to do the same. The concept is that if Tier II maintains their FG buffers to correspond to the buffers of the Tier I suppliers even in terms of transportation time, with appropriate safety by keeping relatively low inventories for local suppliers (3-4 days) and higher inventories for the suppliers that are further away (10 days), with the load being uniform, the supplier can then plan his RM at lower stock levels.

DBM captures changing trends and handles them immediately. This mechanism will change the target levels based on the rate of consumption. Hence, if a stock is continuously in the red zone of the SKU for a larger period of time and that does not affect the supplier’s side, then it is indicative of an increase in demand. When there is an increase in demand, that buffer is increased by a third. On a decrease in demand that is indicated by the stock either being in the green zone or over the green zone for a longer amount of time, that buffer size is decreased by a third. This renders the supply chain highly responsive. As the supply chain becomes responsive, the vicious loop explained in the whiplash effect is avoided. To observe caution, the decrease in buffer size is made only if the decreasing trend is observed for a long period of time, while the decision of increasing a buffer size is taken aggressively on observation for a relatively shorter amount of time.

By employing these methods, Tier I and Tier II suppliers can not only avoid the Whiplash Effect to a large extent, but they can also handle downturns smoothly. The adaptation of this technique requires a software tool that is simple to manage and effective in function. For the drastic changes (> 33%), the buffer sizes may be adjusted manually and having the system take over from those manually set values for further, smaller fluctuations. Such changes occur in times of seasonal changes and such.

D] The Full Kit

Before we set upon the route to employ our solution and right things that seem awry within the supply chain of a firm, we maintain that the firm checks positive on the prerequisites for the solution to work. This is especially vital when changes are prescribed within the setup, where basic requirements such as availability of manpower, production capability and the availability of materials constitute part of the checklist, or the ‘kit’. We run the required analysis against the kit we have assembled which is essentially the checklist of the essential elements. This kit contains every element vital to the application and furthermore the success of the advised solution. Only upon the recipe of the confirmation of a ‘full kit’ do we advance with the applications. This process assures the success of the solution and eliminates excessive variables that will affect the outcome the solution. Based upon the full kit, the aforementioned methodology is then duly applied to the systems and processes of the company’s supply chain. With Aakar Company as well as with other clients we have followed this process to obtain favourable results.

On application of this methodology, we have been able to achieve significant increase in the OTIF by 20% and even 30%. The capacity is also utilised efficiently. Factors such as quality, R&D, etc. need to be well established and the current levels of rejection and rework need to be determined so that appropriate action is taken to tackle these issues simultaneously.

The results that we have been able to achieve for Aakar Foundry on application the aforementioned process are as follows: 

• ADITYA PANDIT - [email protected]