Let’s Go on a Gemba Walk

BLOG 3 Minutes

Imagine we’re taking a virtual “Gemba Walk” through a simple factory layout. The factory consists of a raw material warehouse, seven workstations, and a finished product warehouse.

Unfortunately, we don’t have access to certain critical information, such as the production lead time from raw materials to finished products, the processing time for one item at each machine (known as “Touch Time”), the number of different items processed, or the work-in-process spread throughout the factory

To gather more insights, we decide to speak with the plant manager[1]. The plant manager informs us that the production lead time is approximately ten 8-hour days or 80 hours.

Additionally, the touch time for one item is about 45 minutes, making touch time roughly 1% of the lead time, with the remaining 99% spent waiting to be processed. It’s worth noting that while the factory in question is fictional, many real factories have touch times below 1% of the lead time and most below 10%.

Now, the question arises:

Can we tap into this potential and reduce the lead time? Let’s consider cutting the lead time in half, reducing it from 80 to 40 hours. Consequently, touch time would increase to about 2% of the lead time. This seems promising, but we need to investigate further before making any decisions.

To gain a deeper understanding, we continue our Gemba walk through the factory. Here’s what we expect to observe:

WorkCentre Managers’ Perspectives:

Some managers may complain about not receiving enough material promptly, resulting in their machines idling. This “inefficiency” arises from the output hours falling significantly short of available hours. These managers have little or no material waiting to be processed.

Slower work centres may complain of overload due to a substantial backlog of work awaiting processing. They find it challenging to identify the highest priority order, losing time and capacity searching for the correct one. Their overall capacity is compromised.

Both situations make it difficult for work centre managers to showcase efficiency.

  • Work-in-Process (WIP) Inventory: We anticipate encountering substantial WIP inventory in front of slower machines and after the faster ones. On average, the items in queues spend 79 hours and 15 minutes waiting to be processed, while the actual processing time totals just 45 minutes.
  • Identifying the Bottleneck: We expect to find one machine drowning in WIP, signifying the slowest machine in the system. This machine determines the factory’s capacity and is referred to as the constraint or bottleneck.

Based on our observations, we can conclude:

  1. Wasted Capacity: The massive quantity of WIP causes confusion and wastes the capacity of the slowest machine. This wasted capacity becomes greater when the slowest machine encounters quality problems due to poor upstream machine output.
  2. Scrap Generation: Downstream machines also contribute to wasted capacity by producing scrap. Every scrapped semi-finished product represents a loss of constraint capacity.
  3. Cost of Lost Sales: Ultimately, the biggest cost incurred from these inefficiencies is the lost sales resulting from wasted constraint capacity.
  4. Ineffectiveness in Other Work Centers: We might observe other work centres functioning ineffectively, which (usually) does not waste constraint capacity.
  5. Potential Lead Time Reduction: By cutting the lead time in half, we can reduce the amount of WIP and alleviate the confusion experienced by work centres. The queue shifts to before order release, and a significant portion will disappear. The extent of this reduction depends on how much wasted constraint capacity is recovered.

After our virtual Gemba walk, it becomes clear that improvements can be made in the factory. It is important to note that similar problems can be found in other processes that resemble factory operations, such as processing insurance claims or managing accidents and emergencies in hospitals.

In light of these insights, we should prioritise actions that address the identified issues and aim to optimise constraint capacity, reduce WIP, improve quality, and ultimately cut lead time. By implementing targeted improvements, we can enhance efficiency, increase customer satisfaction, and drive better overall performance in our factory or other similar operational processes.

So, what will you do on Monday?

[1] The cycle on the left describes my Gemba process. The one on the right is a summary of what I expect to find many times.

Published by Rudolf Burkhard

I am a working retiree with about 50 years of experience. My career started and eventually finished at Du Pont. I started in what was called business analysis in their textile fibres department and eventually went into sales. at Du Pont I After several years, I left to run a small company. There I managed to not secure the necessary financing for rapid growth, so returned to Du Pont. During my second stint, I managed to progress to "business manager" before becoming an internal consultant. Independent of the methodologies we used at Du Pont I became enamoured with the various system's management philosophies including the Theory of Constraints. My interest in system's management and the Theory of Constraints led me to leave Du Pont where I was unsuccessful in my attempts to introduce them. Since leaving, I have consulted with various companies using my knowledge and experience to help them boost performance significantly. I am currently with Alkyone Consulting. My target is to keep on consulting and to spread Alkyone's great TOC based software around the World.

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