When investing time and money into lean methodologies, the Theory of Constraints is a crucial process improvement tool that enables businesses to identify, exploit, subordinate, and elevate bottlenecks within their system.
No matter the operation, there are always constraints that limit how much you can produce, deliver, or sell. And in the case of manufacturing, where every action and department is interconnected, the ability to recognize and ultimately alleviate constraints within a system is too good of an opportunity to pass up.
If your business had zero constraints, there would be no limit to how fast or how much you could accomplish.
However, constraints are always with us. But one of the best ways to help you recognize and fix bottlenecks within an operation is to review examples of the Theory of Constraints.
First, What is the Theory of Constraints?
The Theory of Constraints is an improvement methodology that encourages businesses to identify limiting factors (constraints) within their operation. Once a constraint is identified, the goal is to utilize it to its maximum potential and/or elevate its capacity so that it is no longer a limiting factor.
Every manufacturing operation consists of multiple interconnected processes. The weakest link in the process will ultimately set the pace of the production line because the whole operation cannot exceed the limitations of the constraint.
Think of it like a chain. When a chain breaks, it breaks in one spot: the weakest link. This means that while other links may have been able to hold more weight, the entire chain could never hold more than the weight capacity of its weakest link.
It is the same with constraints in a manufacturing operation. While there may be varying degrees of strengths and weaknesses in each department, process, or team, your entire manufacturing operation is only as strong as your weakest link. According to the Theory of Constraints, you can never remove every weak link in a process, but you can progressively exploit or break them to move forward and grow.
For a preliminary example of the Theory of Constraints, imagine you are building electric cars. You have all the pieces except for one key component: the batteries. Due to a material shortage, your company will need to wait an extra month to receive them.
Waiting for the next shipment of batteries is the largest limiting factor within your operation. Even though your cars are practically finished, not one product can be delivered until you receive the batteries and install them.
How to Maximize Constraints: 5 Simple Steps
Applying the Theory of Constraints methodology is surprisingly simple using the following five-step process.
Step 1: Identify the Constraint
Before you can begin maximizing the capabilities of your constraint, you’ll need to find it first. Luckily, there are several telltale signs that point to a constraint within your business.
- Accumulations of inventory before the constraint
- More work in progress than reasonably needed
- Excessive hand holding and oversight are needed to ensure particular processes are performed correctly
- Excessive and/or consistent periods of waiting and machine downtime
To help identify a constraint, perform one or more of the following.
- Perform Gemba walks/audits inspections to visually see signs of the constraint in action.
- Gather data from your work instruction software to review performance data and where slowdowns occur. Look at metrics like lead time, takt time, cycle times, and material usage.
- Look at metrics like Overall Equipment Effectiveness and Overall Labor Effectiveness to pinpoint the exact moment or factor of the constraint.
- Conduct a root cause analysis on the effects of the constraint to find it.
- Ask operators where they see constraints. Your operators are working with constraints every day, so hearing from them is an essential practice.
Step 1 Pro Tip: Quickly gather employee feedback using manufacturing smart forms. Operators can identify issues or make process improvement suggestions straight from their workstations.
Step 2: Exploit the Constraint
Once you’ve found the constraint, the next step is rather simple.
Exploit the constraint to ensure it functions at 100% capacity using your current resources.
An example of this Theory of Constraint step is to imagine a production line where the final assembly takes longer than fabricating the individual parts. While assembly may be the limiting factor on how fast the whole operation can be, you’ll want to make sure that assembly operators are never without the materials they need to keep working.
If assembly workers are waiting for the necessary parts, then the throughput of the constraint will be slower than optimal, resulting in a slower operation overall.
Step 2 Pro Tip: Notice how we’re not yet talking about widening the bottleneck or alleviating the constraint. That will come in step 4. In this step, it is imperative to use current resources to discover and test the maximum capacity of the constraint.
Step 3: Subordinate all Non-Constraints
Step 3 is to ensure that all resources are subordinated to the constraint and facilitate keeping the constraint working at 100% capacity.
In other words, it’s time to look at the factors outside of the constraint.
Since you’ve identified the constraint, it logically implies that non-constraint factors possess a certain degree of excess. Or in other words, they produce more than the constraint since they are not the limiting factor. Without intervention, the excess capabilities of non-constraints would produce buildups of products and potentially contribute to more constraints and bottlenecks within the system.
While this excess of capability may point to an imbalance, it is actually a good thing since they are not limiting the operation. You simply need to enact a measure of control.
We can use this excess to our advantage to apply a drum-buffer-rope system that subordinates everything to the rhythm dictated by the constraint (drum).
- Drum: a constraint that determines the production's tempo and rhythm.
- Buffer: an extra period of time before the drum.
- Rope: when the work order is scheduled to be released.
By carefully planning when work orders are released (rope), manufacturers can ensure that there is a materials/parts buffer that enables the drum (constraint) to always be working. If there is ever a problem in the production line before the drum, you still have a few hours or days' worth of inventory to maintain the constraint's maximum output.
Step 3 Pro Tip: Keep in mind, you don’t want to create too much of a buffer before the assembly process. While a small buffer can be a good idea, a significant pile-up of pre-fabricated parts might cause space and safety issues in your facility, contributing to another constraint. Better to employ Just-in-Time (JiT) with as small a buffer as possible to facilitate departments receiving their resources.
Now, in step 4, we can go further than maximization and take action to elevate and/or break the constraint. However, this process often requires serious changes like the redistribution of resources or investment in new technologies.
When making a change to your operation or investing in new technology, it is important to stick to the goal of increasing the throughput of the operation. If not, you may make changes that benefit other areas but do nothing to elevate the performance of your constraint.
Now while the changes you make will be specific to the problem at hand, a few key methods will help you maintain your goal. Use the following measures to break your constraints and monitor your goals.
- Establish repeatable best practices: Ensure that every operator is performing their tasks and responsibilities the right way. Standardization is crucial when trying to pinpoint areas for improvement.
- Analyze Key Performance Indicators: Further, pinpoint the key contributors to the constraint by looking at the performance of specific metrics and calculations that accurately represent the performance of the constraint.
- Perform Time Studies: Create timestamps with the process to track the exact times that certain actions are performed within the constraint.
- Evaluate Resources: Sometimes, our current equipment and tools could be lacking the necessary capabilities to sufficiently break a constraint. For instance, if you have a high turnover within your workforce, investing in training software that actively guides workers through the process can make all the difference.
The goal of this step is to increase the performance of the constraint so that the identified area is no longer the weakest link.
Step 4 Pro Tip: Use work instruction software to perform the above 4 crucial steps. Create standardized procedures, analyze KPIs, perform time studies, and more within one system.
Step 5: Repeat
Like all other lean methodologies, the Theory of Constraints is an improvement plan that needs to be implemented and then repeated continuously. There are two scenarios in this step:
- The constraint has been broken: As one constraint is identified, exploited, subordinated to, and elevated, new constraints will take its place as the weakest link within the operation. These new constraints can then be managed by repeating steps 1-4.
- The constraint is not broken: If the constraint has not been broken, then you’ll need to repeat the process. Often this can be a result of misidentifying the constraint. Return to step 1.
It is crucial to remember that the 4 previous steps are not a one-time action. Rather, they are an ongoing process that enables businesses to evolve and grow.
3 Examples of the Theory of Constraints
Let’s finalize what we’ve learned about the Theory of Constraints and apply it to real-world scenarios that affect manufacturers.
Keep in mind that the above 5 steps can vary greatly depending on the operation and industry. This means that some scenarios will only be able to experience full exploitation and/or subordination rather than completely elevating/breaking the constraint.
Theory of Constraints Example #1: Drum-Buffer-Rope & Work Orders
Improperly managing time is often a huge constraint for many businesses, especially companies with vertically integrated production lines where multiple parts are fabricated before moving on to the final assembly.
For this Theory of Constraints example, think of a camera sensor and lens for state-of-the-art videography drones.
The camera sensor takes 30 minutes to fabricate while the camera lens itself takes close to 60 minutes to create - almost twice as long as the sensor. If you let each process run its course without intervention, the assembly department would have a buildup of camera sensors while constantly waiting for the lenses.
To mitigate waiting and pileup of stock, you could issue the work order for the camera sensors 30min after the lens work order has begun. This should allow both pieces to arrive at the assembly department at the same time and effectively subordinate all non-constraints.
However, this idea is somewhat incomplete as it leaves little room for any fluctuations or issues.
Instead, by understanding the tenets and tools of the Theory of Constraints, deploying a drum-buffer-rope system subordinates all non-constraints to the maximum potential of the current constraint while introducing flexibility.
First, identify the constraint (drum). In this case, the constraint is the camera lens process. The rope is used to issue work orders in advance of the constraint and buffer. Since other non-constraints are faster, the lens process will set the pace of production. But we can maximize the constraint's capacity and flexibility by applying one of two types of buffers.
Parts Buffer: Each day, maintain a small stock of camera lenses that are ready for the assembly process (rope), ensuring that the assembly department has the number of lenses they need for the day. This way, even if there are unforeseen issues, you still have some stock to maintain the constraint at maximum capacity.
Time Buffer: Here you would issue work orders for the camera lenses slightly in advance of the camera sensors. If the lens takes 1 hour to fabricate, you could create a buffer that ensures the lens work orders are issued (rope) 2-3 hours in advance of the assembly process. This head start enables the assembly department to keep a small yet ever-growing inventory that should deplete itself by the end of the production period. Despite adding more time to the total process, we are simply starting work earlier than needed to protect the operation from unforeseen issues while maximizing the potential output of the constraint.
Choosing between a time buffer or a parts buffer will ultimately depend on the specific requirements and capabilities of the manufacturing operation and business.
Theory of Constraints Example #2. Slow Quality Inspections
While production can often be a major focus within the Theory of Constraints, other areas add complexity, resulting in a slower operation overall. One such activity that companies struggle with is quality inspections.
For instance, imagine your company is assembling toy cars for children. Since this is a children's toy, several quality guidelines must be followed. Final quality inspections have been a major drain on time, creating a constraint with a significant backlog of products waiting to be inspected.
To maximize the constraint, you’ve applied the 5 steps of the Theory of Constraints methodology.
- Identify that the constraint is within the final quality inspection process.
- Exploit the constraint to ensure that final quality inspection personnel are never waiting for products to inspect.
- Subordinate all non-constraint activities to the speed and tempo of the quality inspection process. In this case, you may need to slow down the speed of toy car production.
Organizing these three steps properly will give you some time and space to properly evaluate your decisions for the 4th step.
- Elevate the constraint by investing in tools and training to speed up the rate of inspections along with the number of people that can perform the quality checks. Work instruction software enables employees to quickly learn how to perform inspections while also directing experienced employees with the best practices for the inspections.
- Repeat the process to verify that the constraint has been broken. Then identify the new constraint and continuously improve the operation.
Theory of Constraints Example #3. Finding 2 Fluid Constraints
Sometimes, rather than existing within one section of a process, a constraint can be found within a fluid part of your operation, such as the workforce or the machinery itself.
For this example of the Theory of Constraints, imagine you run a high-mix/low-volume manufacturing operation. While some contracts are repeated, it has become increasingly challenging for your operators to remember the ins and outs of every job, creating several potential constraints within each product line.
In this case, like in our earlier example, you decide to follow the 5 steps of the Theory of Constraints.
- Identify that in most departments, the constraint is within the human processes.
- Then, exploit the constraint to maintain maximum capacity by providing additional training when needed.
- After, subordinate all non-constraints to set the proper tempo for production with the current methods and workforce capacity.
While the constraint has been properly exploited, the production speed is still too slow.
- In this case, invest in work instruction software so that every worker has the right knowledge they need at the right time.
- Then repeat the process to evaluate if the changes were successful.
Lo and behold, they were. But now you’ve already noticed the next constraint that needs to be developed.
By using your work instruction software and monitoring employee performance, you see that certain machines are often sitting inactive, greatly limiting the efficiency of the operation and creating a new constraint.
In this case, you repeat the 5 steps above.
- You identify that inefficient planning of machine usage is the current largest constraint.
- Exploit the constraint by optimizing the machine usage plan.
- Subordinate all non-constraints to set the proper tempo for production with the current methods and equipment capacity.
Similarly, the constraint has been properly exploited but the production speed is still too slow.
- Elevate the constraint by using advanced systems and tools to create an intelligent machine layout and schedule.
- Then repeat the process to evaluate if the changes were successful.
