A bottleneck is a process in which its limited capacity retards the whole chain’s capacity. This assignment provides a reflective view of learning regarding bottleneck’s impact on process metrics of the manufacturing facility. Changes requires as an operational manager for maximizing capacity per hour are also identified without purchasing additional workstations.
Amaral (2014) stated that Bottlenecks are usually constraints that take the longest time in a supply for a particular demand. In the simulation three-step model, workstation B assigned to Bob is the bottleneck of the supply chain process. Due to the bottleneck, I have learned that workstation A is blocked and as a result, workstation C is blocked too for additional 5 minutes. Workstation A assigned to Alice and workstation C is assigned to Charlie having different task time in units, which are 3 minutes for workstation A, 5 minutes for workstation B and 2 minutes for workstation C respectively.
Using the simulation, no matter where the bottleneck is used that is the workstation B with 5 minutes times is placed, overall capacity per hour remains same at a constant rate of 12. A total utilization percentage of 66.67% is calculated. However, when the bottleneck is placed at mid position after workstation A and before workstation C, the task at workstation A is delayed during processing of workstation B. Hence, it is recommended to place workstation B at starting of the supply chain followed by workstation B and workstation C respectively. With such arrangement I have learnt that the throughout process was increased. However, process metrics was not influenced significantly.
The bottleneck working at 100% utilization increased the capacity per hour and overall utilization although the other two workstations were not working at 100% utilization but at 60% (Workstation A) and 40% (Workstation B) (Kjellsdotter Ivert 2014). Overall utilization remains to be an average value of 66.67%. The cycle time remains 5 minutes because as a task is assigned to Alice, it takes 3 minutes to process, then after it is passed to Bob, it takes around 5 minutes to process when the task at A is blocked. Hence, I have learnt that cost per hour on a bottleneck is numerically equal to loss of an hour for the entire supply chain and equal to the loss of throughout for the supply chain as a whole (Rotaru 2014). When I recognized the bottleneck, incurred a total cost of 0.1% of the total cost, rest of the 99.9% can be used for spending in increment of the throughout without any extra cost to be incurred (Cb.hbsp.harvard.edu 2017).
As an operation manager, first I would like to rearrange the workstations. According to Costas et al. (2015), if the task time is constraints then it will be difficult to obtain a higher capacity per hour. However trying to decrease the task time in minutes will increase the production per hour dramatically. If the utilization percentage of each workstation is to increase, I need to find a way to decrease bottleneck’s time duration. Since the bottleneck is working at 100% efficiency, other workstations are providing maximum utilization (Stadtler 2015).
If the workstation B’s task time is decreased to 2.5 minutes, the utilization is decreased to 83% and hence the workstation A gets a full utilization of 100%. Simultaneously, workstation B has a comparatively lower utilization of 67%. The capacity per hour in this scenario is increased to 20 and a total utility of 83.33% is achieved hence an improvement of 16.66% extra from initial condition is achieved. Cycle time is also decreased to 3 minutes as well as minimum throughout cycle is 7.5 minutes.
Most importantly maximum utilization will be achieved if all the workstations are made to have an equal task time of 3.33 minutes as average working time for Alice, Bob and Charlie are 3.33 [(5+3+2)/3 = 3.33]. Therefore, 100% utilization is achieved due to removal of bottlenecks and a min throughout time of 10 minutes is achieved. Capacity per hour is also improved to 18 with a total utilization percentage of 100% (Cb.hbsp.harvard.edu 2017).
However if the task time cannot be changed or altered and there is only option to interchange the position of workers in workstation, I would prefer Bob the slowest to start the chain followed by next slowest Alice and finally Charlie the fastest. This will ensure that no goods are retained in the factory process chain and are delivered to logistics as soon as they arrive at workplace (Roehrich 2014).
If the task times cannot be changed and workstations cannot be interchanged, I would decrease the input to bottleneck steps. Moreover, I would ensure that everything provided to the bottleneck is free from any sort of defect. As stated by Kerzner (2013), valuable bottleneck resources will not be used up in this way to process materials, which will be discarded later on. Any activities, which can be done by other machinery or personnel, will be removed from bottlenecks. I will also assign most productive member to the bottleneck process and reinforce it with latest technology. I will also add capacity to the bottleneck process. Adding capacity to bottlenecks will ensure that the supply-chain management process is enhanced to maximum proficiency level increasing production output.
It can be concluded that by simply shifting the work, process efficiency can be improved significantly without the application of additional cost. Specialized job roles if assigned will however create problems, as the job cannot be shifted. In the above simulated process, if the work is possible to be shifted from one workstation to another workstation, it is recommended to keep the bottlenecks at the initial step or provide finished product to the bottleneck so that no resource of the bottleneck is used. In addition, if the shifting is not possible, it is recommended to use efficient machine and worker for the bottleneck task. Most importantly if bottleneck task is used is not scheduled properly will delay the entire process. It is also seen that as an operational manager I will try to resource and level time of each workstation that will cause to obtain a greater production rate and increase utilization percentage.
Amaral, T.M. and Costa, A.P., 2014. Improving decision-making and management of hospital resources: An application of the PROMETHEE II method in an Emergency Department. Operations Research for Health Care, 3(1), pp.1-6.
Cb.hbsp.harvard.edu, 2017, Process Analytics Simulations, Available at: https://cb.hbsp.harvard.edu/cbmp/context/coursepacks/61182556 [Accessed 1 April 2017].
Costas, J., Ponte, B., de la Fuente, D., Pino, R. and Puche, J., 2015. Applying Goldratt’s Theory of Constraints to reduce the Bullwhip Effect through agent-based modeling. Expert Systems with Applications, 42(4), pp.2049-2060.
Kerzner, H., 2013. Project management: a systems approach to planning, scheduling, and controlling. John Wiley & Sons.
Kjellsdotter Ivert, L. and Jonsson, P., 2014. When should advanced planning and scheduling systems be used in sales and operations planning?. International Journal of Operations & Production Management, 34(10), pp.1338-1362.
Rotaru, K., Churilov, L. and Flitman, A., 2014. Can critical realism enable a journey from description to understanding in operations and supply chain management?. Supply Chain Management: An International Journal, 19(2), pp.117-125.
Stadtler, H., 2015. Supply chain management: Supply chain management and advanced planning. Springer Berlin Heidelberg.
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