The Theory of Constraints is a well-known managerial theory for manufacturing and production system enterprises. Constraints are factors that limit the operational capacity of a manufacturing facility and it is the job of managers to remove these barriers in order to increase outcome and profit. The theory is essential to advanced scheduling and utilization in manufacturing, improving the efficiency of businesses on a practical level. This report will investigate the fundamentals of the Theory of Constraints, apply it to a manufacturing process, and examine the associated challenges involved in the process.
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The Theory of Constraints is a manufacturing methodology that seeks to identify and resolve a limiting factor (constraint) that is reducing the throughput of production in some manner thus creating a barrier to achieving an operational objective. It was created by Dr. Elyahu Goldratt in 1984 by introducing it into production management, where it eventually became one of the most well-known practices.
The theory attempts to systematically resolve the constraint until it no longer limits the process. The theory takes on a practical and scientific approach to making changes, hypothesizing that any complex manufacturing system consists of multiple simpler elements that act in a chain. Therefore, the framework offers a variety of tools including five focusing steps, the thinking processes, and throughput accounting to create improvement (Costas, Ponte, de la Fuente, Pino, & Puche, 2015).
Application to Objective
A selected objective for the application of the Theory of Constraints is improving shipping times of products for a midsize steel manufacturing facility. The facility is experiencing a bottleneck in the manufacturing process which is leading to it being unable to meet planned production targets. The first step using the theory would be to identify the constraint by examining the whole production plan and following the manufacturing process.
This allows us to pinpoint the resource or stage which is creating the bottleneck, as according to Goldratt theory is the limiting factor to the throughput of the entire plant. In the scenario, the bottleneck is in the middle of the manufacturing process when the steel strips undergo sizing modification into width and thickness clusters. The second step is to utilize the constraint by creating a quick fix using available resources.
Potential interventions include continuous operation by scheduling workers shifts during breaks and overtime to prevent backup and internal offload that would deviate constraint work to other machines even if they are not optimized for the specific purpose of strip production.
The third step is to subordinate and synchronize the constraint, which focuses on non-constraint equipment. The key is to upstream the equipment with excess capacity so that the constraint buffer is consistently filled but not overloaded. Implementing techniques such as a drum-buffer-rope (DBR) and priority maintenance can help to synchronize production in a manner that would ensure steady operation. The fourth step is to enhance the performance of the constraint by making sustainable changes that would eliminate the bottleneck. These changes are long-term and may require significant investment.
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In the scenario, it may be viable to reorganize the manufacturing plan and implement a regression model that would predict throughput based on strip characteristics, eliminating the constraint and optimizing strip output by their grade depending on the shift (Schmedders & Schulze, 2017). Finally, the last step is to repeat the whole process to ensure the changes are not a one-time resolution but serve as a continuous improvement process and evaluation of the identified constraint.
By applying these five steps to the objective, one of the inherent outcomes will be boosted profitability. The Theory of Constraints improves profitability by appropriately redirecting enterprise and manufacturing resources that increase restricted contribution margin, reduce inventory, and minimize operating expenses. Furthermore, the theory is commonly implemented alongside lean manufacturing and accounting which contribute to efficiency, optimization, and quality management (Okutmuş, Kahveci, & Kartašova, 2015).
In the scenario, identifying the constraint can greatly increase the output of the manufacturing process, thus enhancing both quality (introduction of automation rather than manual work) and shipping times. Alongside competent management and sales, firm profits can increase exponentially through this method of continuous improvement.
Despite the usefulness of the theory, there are a number of inherent limitations that should be noted. Beginning with the principle of identifying and resolving the biggest constraint in production which requires managers to focus on either mitigating or removing it. However, while the sole focus is on that constraint, it may lead to other constraints arising which reduces the overall effect. The identification process itself is challenging since there are no specific steps to doing so.
In a modern and complex manufacturing facility, there are a number of synchronous parts. Therefore, an identified constraint may be a consequence of a less obvious factor or be irrelevant to the bottleneck at all. However, the theory still forces a dedication of resources to the issue. Another aspect is that the theory does not consider external variable factors that may be impacting the manufacturing, such as market demand that may influence product outputs. Finally, the theory is limited only to the current time frame and manufacturing process, focusing on short-term solutions when addressing any given constraint (Eidelwein, Piran, Lacerda, Dresch, & Rodrigues, 2017).
Managers can deal with arising constraints by looking at the manufacturing process more broadly and attempt to not shift focus away from other stages of production while resolving a specific constraint. Furthermore, utilizing the theory’s concept of continuous improvement benefits performance outcomes. Identification issues can be resolved by conducting regular checks and evaluations of all manufacturing stages, as well as consistently monitoring and collecting data.
Therefore, when problems arise, it will be much easier to pinpoint the location. Variable factors can be mitigated by utilizing external data such as market studies to complement the information derived during the application in combination with manufacturing data such as batch size (Golmohammadi, 2015). Finally, to overcome time frame limitations, a manager should focus on long-term effects when attempting to resolve constraints, with the strategy that the solution will have a long-lasting impact on the manufacturing and business variables.
Costas, J., Ponte, B., de la Fuente, D., Pino, R., & Puche, J. (2015). Applying Goldratt’s Theory of Constraints to reduce the Bullwhip Effect through agent-based modeling. Expert Systems with Applications, 42(4), 2049–2060. Web.
Eidelwein, F., Piran, F. A. S., Lacerda, D. P., Dresch, A., & Rodrigues, L. H. (2017). Exploratory analysis of modularization strategy based on the Theory of Constraints thinking process. Global Journal of Flexible Systems Management, 19(2), 111–122. Web.
Golmohammadi, D. (2015). A study of scheduling under the theory of constraints. International Journal of Production Economics, 165, 38–50. Web.
Okutmuş, E., Kahveci, A., & Kartašova, J. (2015). Using theory of constraints for reaching optimal product mix: An application in the furniture sector. Intellectual Economics, 9(2), 138–149. Web.
Schmedders, K., & Schulze, M. (2016). Solid as Steel: Production Planning at thyssenkrupp. Web.