Any manufacturing company’s success is dependent on how well its resources perform, in other words the level of performance of its factory. The factory’s performance is in turn constrained by the manufacturing infrastructure and is hence designed so as to suit the company’s strategy related to the products and their quantities. Production management essentially takes the company’s strategic requirements in terms of its key competitive objectives, for instance shorter lead time, low cost etc., and translates them into schedule for the factory environment in terms of inventory, job sequencing and time table etc., so that these objectives are met (Childe, 1997, p.28).
In an industrial environment, there are always constraints that affect the throughput of a system in terms of quantity or quality of product delivered or the delivery time (Lange & Ziegenbien, 2005, p.1).Some of these constraints are bottlenecks i.e. resources whose availability is less than the demand placed on them, while others are potential bottlenecks or Capacity Constrained Resources CCRs i.e. resources who utilization is close to capacity and in case of non-optimal utilization may become bottleneck (Telsang, 2002, p. 518).
Theory of Constraints was developed to address such practical problems in manufacturing. This theory given by Goldman and Cox in their famous book Goal is basically a productions and operations management strategy dealing with the CCRs i.e. potential bottlenecks in an industry environment (Quassin, 2000, p.3).
According to Goldman and Cox, the goal of all the manufacturing companies is to make money (quoted, Childe, 1997, p.29). Hence according to them the success for any manufacturing company would come if they can properly identify the aims to their business and then deal with the constraints which would prove to be present or potential bottlenecks in achieving the goal (Childe, 1997, p.115)
The Theory of Constraints was developed in over a decade’s period, by the Israeli Physicist Dr. Eliyahu M Goldratt based on his observations of certain common characteristics that effect system operations (Dettmer, 1998, p.11). This combined with his thoughts comprises the Theory of Constraints TOC, which is a collection of principles, a set of generic tools and the specific applications of these tools.
The principles explain the management actions and the various interactions between processes. The tools are methods that can be used to apply these principles in specific instances, while the applications are the instances where these tools have been successfully applied in these situations many times so that they can be considered as generic solutions to the problems. Hence, the TOC is still evolving to this day (Dettmer & Schragenheim, 2000, p.13).
Among the principles of TOC, the most basic are three key assumptions about constraint management, five focusing steps to guide the system and three measures to assess whether the actions being taken at the local level are producing the desired results at the global level.
Assumptions – TOC is based on three interrelated premises:
Every system has a goal and asset of necessary conditions that must be satisfied if the goal has to be achieved,
The overall system’s performance is more than just the sum of its component performances, and
Very few factors or constraints, often only one, limit a system’s performance at any given time
(Ronen, 2005, p.21)
Five Focusing Steps – Goldratt created five steps as a way to make sure that the management focuses on the process for continuous improvement
Identify the system’s constraint,
Decide how to exploit the system’s constraint,
Subordinate everything else to the decision taken in the step above
Evaluate alternative ways to elevate the constraint
Return to the 1st step in case the system constraints have been changed
(Srinivasan, Jones & Miller, n.d., p.136)
Evaluation – The evaluation of the operating decisions can be done by the three financial yardsticks which are provided by the constraint theory – Throughput (T), Inventory or Investment (I), and Operation Expense (OE) (Dettmer & Schragenheim, 2000, p.40). These form the yardsticks because as mentioned earlier, according to Goldman and Cox, the goal of all the manufacturing companies is to make money (quoted, Childe, 1997, p.29)
Question 2: Describe how TOC can help to prioritize the most profitable high impact initiatives within a production environment
The use of Theory of Constraints in the production management was initially done to solve the problems of bottlenecks, scheduling and inventory reduction (Wang, 2002, p. 149).
Industry’s aim to achieve the goal of making money has been traditionally achieved by reducing the operating costs. The logic is that every dollar that is saved adds up to the profit. A compelling reason for adopting such a measure is that the costs can be controlled. The next step is to reduce the inventory while increasing the throughput is the last priority with the production managers.
Japanese saw the value that can be achieved by reducing the inventory and hence put this as their first priority. They developed what is known as the Just-in-Time philosophy. For doing this the pipeline needs to be kept flowing i.e. a pull phenomenon, which correspondingly increases the importance of increasing the throughput to being the second highest priority (Dettmer & Schragenheim, 2000, p.44).
However, according to Goldratt’s Constraint theory, the highest priority should be given to increasing the throughput, while reducing the inventory or investment should have the second priority and reducing the operating expense should be the last priority (Bushong & Talbott, 1999, p. 2). The reason for this is in the traditional methods, the production managers were assuming that an infinite amount of hours were available in each factory’s work and machines, which is not practically possible.
Hence, Goldratt began by assuming that the manufacturing company is essentially a system with machines and people available for finite periods of time per day or week or month. He further assumed that at any instant in time only one factory or resource could prove to be a bottleneck in achieving the goal of making money. Hence, it followed that if this bottleneck was running to its full capacity, increasing the speed of the other centers would not do any good, as the speed of this particular centre would not increase (McMullen, 1998, p.105).
This can also be explained as follows. Theoretically the any of the constraints could vary from zero to infinity, but practically the operating expense and inventory cannot be reduced under zero, neither can the throughput be increased till infinity. However, the practical limits for reducing the operating expense and the inventory are actually much higher than zero.
This is because the manufacturers have to spend money on them in order to make money from the end products using these investments as inputs. While the practical limits for increasing the throughput is still much less than infinity, but its potential for adding up to the profits is much higher than the potential to do the same using cost-cutting. Cost-cutting is also risky in nature, because there is always the danger of spending less than what is required which would directly impact on the quality, and hence the inventory too in the long run (Dettmer & Schragenheim, 2000, p.44).
The management philosophy of Theory of Constraints can hence be viewed into three separate areas which are interrelated: logistics, performance management and logical thinking. Logistics includes the drum-buffer-rope scheduling, buffer management and VAT analysis. Using these tools, the tasks are scheduled in a production environment and prioritized.
The next area is the Performance measurement which includes the Throughput, Inventory, the operating expense and the five focusing steps which have been discussed earlier. The thinking process tools help in identifying the root-problem (current reality tree), identifying and expanding win-win solutions (evaporating clouds and the future reality tree), and developing the implementation plans (prerequisite tree and transition tree) (Stein, 1997, p. 199).
.DBR Scheduling – The basis for the DBR or drum-buffer-rope scheduling is the factory’s primary constraint which could be a present or potential bottleneck. This primary constraint acts as the drum for the DB scheduling. This scheduling process produces the schedule of what jobs to be produced and in what order on the drum.
A time element known as the buffer is then used to establish the realistic commitment dates for the operation and its deadline. Another time element called the rope determines the schedule for introducing additional tasks and materials into the work process flow of the operation. Each task or batch in the drum schedule has a buffer and a rope time element. There are other time elements in the buffer also which when taken as a group form the time buffers (McMullen, 1998, p.106).
This DBR scheduling process synchronizes the entire work throughout the factory, and creates a synchronized manufacturing state by basing all the schedules on the drum schedule or the bottleneck. In addition to this, it also provides feedback and control process which is known as buffer management. The function of the buffer management system is to ensure that all the other factory resources which are non-constrained are working on the right jobs, at the right times in the sequence, and in the right production batch quantities such that the schedules are supported from the drum task and customer deliveries are met.
Finally all the non-constrained by definition have some spare capacity. While this is not excess capacity and can be used in the productive or protective sense, the scheduling of these is also important so as not to have excess inventory or investment condition. This is taken care by introducing the time buffers, discussed earlier, in the DBR schedule such that no production is lost at the drum. The extension of this process into the dynamic buffering can be used for fine-tuning the extra capacity (McMullen, 1998, p.107).
Hence, this scheduling process reliable delivery schedules for the customers, because the schedules are based on finite capacity assumption instead of the erroneous infinite capacity assumption (Bushong & Talbott, 1999, p. 3).
Question 3: Discuss how you will implement the proposed philosophy in order to rescue a sick hypothetical organization
The prior section dealt with the drum-buffer-rope i.e. DBR scheduling, which is the TOC production planning methodology. As the aim of the TOC is to see to it that the constraint does not effect the production schedule, the DBR takes care of the weakest link i.e. the drum, schedule i.e. the buffer, and deadline i.e. the rope (Greeff & Ghoshal, 2003, p. 70). In addition to the DBR scheduling, a buffer management scheme was also described above, which is needed to monitor the entire process.
In the tradition approach, the DBR scheduling was used as the planning process and the buffer management was used to monitor the plan’s progress. In the present scenario, the DBR and buffer management process are dynamic and offer continuous feed backs to the production manager so that he can improve upon the system.
As was mentioned in the first section, throughput is the primary are of focus of the TOC arrangement. The throughput is the money generated by the system after taking out the external costs, and this should be maximized for the profits to increase according to the theory of constraints. However, the implementation of TOC is not very easy in a practical situation, and in many cases it necessitates a change in the entire way a company operates. This difficulty can be explained by a simple example as follows.
A company has identified that for increasing the its throughput, there is a need for producing the product and selling it with the lower sale price per product unit. As of now the company compensated its sales forces on a commission basis, based on the percent of sales and the people in this department try to sell their products with the highest sales price. This means that the company would need to develop an entirely new way of compensating its sales force. There might be further problems if the arrangement is not satisfactory enough to the sales people, which might lead to a drop in the sales – quite opposite to the goal of the company.
Care should also be taken to remember that TOC is a dynamic management process. This means that the task does not end after finding out the constraint. On the contrary, the management should continuously analyze to see if this factor can be increased or some other factor might become a constraint. Such analysis should be made regularly and the options should be revised. In addition to this, continuous analysis should be made to check the operating expenses and inventory and investments should also be minimized (Bushong & Talbott, 1999, p. 4).
The above theories will be explained by taking an example below. First the basic system application is given using the TOC to explain the various constraints of the system. After this the complete system is shifted to a plant, which is a sick unit and steps are given to convert this plant into a optimal unit.
Basic System and Constraints
The example has a manufacturing unit which is essentially a machine that cuts silicon wafers into individual chips (Anderson, 2003, p. 30). The number of wafer cut by this machine in a unit time without getting overloaded is the constraint of the machine and the primary constraint of the entire manufacturing system. For instance, the machine can cut on 100 wafers per hours. In this case, it would be immaterial to get more raw materials since the constraint would still not be affected in this case.
Now that the constraint of the system has been identified, a decision must be made on how to minimize its constraining ability on the system. The utilizing capacity of the constraint must be maximized i.e. the Capacity Constrained Resource, in this case the machine, must be fully utilized and must never be idle. Every unit of production that is lost on this system is a unit lost to the complete system (Anderson, 2003, p. 29).
This constraint can be protected from being idle by providing a buffer or queue of raw materials for it to cut. For this example, let us assume that each wafer can be cut into 25 chips. That is to say 4 wafers would be needed by the machine per hours. This follows the generalization that the constraints are protected by buffers. The queue of silicon wafers in this case would be physical buffer of inventory.
In addition to this protecting a constraint is a necessary part of exploiting a constraint to the full (Anderson, 2003, p. 29). In case of the manufacturing system, the manufacturing unit can be protected from starvation or idle moments, by providing a buffer of silicon wafers. The unit also needs to be protected from power interruptions and surges, by providing a uninterruptible power supplies, and further giving a backup generator.
The manpower related constraint can be sorted out by working the machine in three shifts by people of eight hours each, so that the machine is utilized for 24 hours per day. Finally the quality related issues can be sorted out by performing a quality check on the wafers prior to being set on the queue, to ensure that only good quality wafers are passed on to the manufacturing unit.
In case of TOC care should be taken to ensure that subordination of all the activities are obtained to take care of the constraint (Anderson, 2003, p. 31). As can be seen in the example a decision is taken to see that the manufacturing unit is the constraint of the system, a and hence steps have been taken to take care of this constraint and utilize he machine for obtaining the maximum productivity.
Ti subordinate all other activities to this decision, the flow of inventory should be regulated from the factory gate to the wafer cutting machine. The rate of sending the wafer to the machine should be same as the rate of the machine to entirely cut the wafer. Here, the rate of the cutter is the drum. The inventory of the factory gate to the cutter is the rope and a buffer in front of the cutter to prevent it from getting idle is the buffer.
Plant as a Sick Unit
Suppose that there are 10 such systems in a plant which is a sick unit. There are problems with excess inventory, the quality of wafers produced, the throughout is varied and is not stable and there are problems with delays between the operations with long periods where the machines are idle and others where there is extra load on the machines.
The primary problem here is to streamline the operations. The basic constraint is already mentioned in the prior section i.e. the number of wafers that can be cut by a unit. This cannot be changed and must be utilized to the maximum. All the remaining actions must be subordinate to this activity such that the constraint or the drum is taken care.
First of all the machines as a total can process 1000*10 =1000 wafers in a hour, which means 4*10 = 40 wafers must be passed to the machines per hour (as each wafer can be cut into 25 chips). Now that this has been decided, the queuing systems should ensure that the wafers are taken from the resource gate and passed to the machines. The easiest way of doing this would be to pass 4 sets of wafers per hour, after every 45 minutes 4 more wafers would be passed to the machines. This means that there would be enough time for checking the quality of the wafers and passing them to the machines, without worrying about the exact synchronization of each wafer to rate at which a machine cuts them.
This would also take care of the idle periods of the machines, as in this case the machines would always have one wafer to cuts, by which time the other 4 wafers would be sent to it. The inventory would be controlled too. In addition, the throughput would be at a constant rate. Finally, the technique would also ensure that the burden on the quality checkers and machine operators is minimal.
In the former case, the quality checkers could have a quality check wafers ready for a couple of hours advance, which would be passed to the machines every three quarters of an hours, which means these people do not need to be on job 24 hours a day. Also, the machine operators would have more time to check the power supply and other maintenance issues, while checking if the new wafer lot has been passed or not.
The above example gives the implementation of Theory of Constraints method to a sick unit, to make it operate in an optimized way. The example taken is a very simplistic application which can be solved easily using the single DB technique.
Anderson DJ, 2003, Agile Management for Software Engineering: Applying the Thoery of Constraints for Business Results, New Jersey: Prentice Hall PTR
Childe SJ, 1997, An Introduction to Computer Aided Production Management, 1st Edition, London: Chapman & Hall
Dettmer HW, 1998, Breaking the Constraints to World-Class Performance, Milwaukee: ASQ Quality Press
Dettmer HW, Schragenheim E, 2000, Manufacturing at Warp’s Speed: Optimizing Supply Chain Financial Performance, Florida: CRC Press
Greeff G, Ghoshal R, 2004, Practical E-Manufacturing and Supply Chain Management, Oxford: Elsevier
McMullen TB, 1998, Introduction to the Theory of Constraints (Toc) Management System, Florida: CRC Press
Ronen B, 2005, The Theory of Constraints: Practice and Research, Amsterdam: IOC Press
Stein RE, 1999, The Theory of Constraints Applications in Quality and Manufacturing, New York: CRC Press
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Bushong JG, Talbott JC, 1999, The CPA in Industry: An Application of the Theory of Constraints, The CPA Journal, April 1999 Issue, http://www.nysscpa.org/cpajournal/1999/0499/Departments/D530499.HTM, Article Accessed on 18th September 2007.
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