Theory of Constraints

Topics: Theory of Constraints, Eliyahu M. Goldratt, The Goal Pages: 11 (4208 words) Published: April 2, 2013
The Theory of Constraints and Drum–Buffer–Rope
Drum – Buffer – Rope (DBR) is an operations scheduling methodology based on Dr Eli Goldratt’s Theory of Constraints (TOC) and first written about in The Goal and further explained in The Race. Drum Buffer Rope is just one part of the TOC Operations solution; it is the machine that sets the plan for Operations. However the second part of the TOC Operations solution is Buffer Management. Buffer Management is the monitor and control mechanism that ensures the machine is running well in execution. Theory of Constraints takes a systemic view of a company or organisation. This means it treats the organisation as one and not as a number of different departments. An organisation is made up of a set of interdependent elements working together to achieve a company goal or objective. It is, therefore, important to relate all actions within an organisation to its impact on the global objectives. It is also important to realise that not all elements affect the system in the same way; some elements have less capacity than others. The elements with less capacity are the constraints of the system and limit the system’s ability to achieve its global objectives. If a (for profit) organisation had no constraints, then its profit would be infinite. In reality, there are very few constraints to any system. The 5 Focusing Steps

Theory of Constraints uses this view to derive a 5 step process, called a ‘Process Of On-Going Improvement’ (POOGI), to improve any system. These steps are called the 5 Focusing Steps: (Step 0 – Define the system’s goal or objective)

Step 1. Identify the System’s Constraint(s).
Step 2. Decide how to Exploit the System’s Constraint(s). Step 3. Subordinate everything else to the above decisions. Step 4. Elevate the System’s Constraint(s).
Step 5. If in the Previous Steps a Constraint has been Broken, go back to Step 1. (Warning: Do Not Allow Inertia to Cause a System Constraint) The difficulty in Operations
In production, many different scheduling approaches are used to attempt to manage the capacity of the system and protect the system from the impact of variation (Murphy’s Law), so as to deliver the product or services “on time”. The difficulty facing operations environments is to find a solution in environments where demand is fluctuating, Murphy strikes frequently, variation is everywhere and conditions rarely remain constant. Just In Time (JIT) provides one solution to this problem. The JIT philosophy holds a minimum inventory between each work-center, typically only one. When there is a blockage in the flow line and Murphy ‘strikes’, the line stops and plant output is effected. This output can never be recovered by the system as in most cases the flow line is balanced. Just-in-time does an excellent job of minimising inventory in the system thus increasing the flow and minimising the lead time. However it assumes variation in the process and capacities are minimal and focuses on reducing this variation everywhere. Drum-Buffer-Rope enhances JIT by protecting the weakest link in the system, and therefore the system as a whole, against process dependency and variation and thus maximises the systems’ overall effectiveness.  The outcome is a robust and dependable process that will allow us to produce more, with less inventory, less rework and defects, and better on-time delivery – always. Applying the 5 Focusing Steps

Following step 1 – Identify the System’s Constraint(s), it is important to determine where the constraint in the system lies. With operational environments, the constraint can either be internal or external. If there is more market demand than the system capacity then there is an internal capacity constraint. If there is more capacity available but orders are not available to process then the system has an external market constraint. For production companies with a true internal constraint Drum–Buffer-Rope (DBR) is the preferred solution. For...
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