Managing V - Plant Material Flow Configuration
Image courtesy Dr. Kelvyn Youngman https://www.dbrmfg.co.nz/Production.htm

Managing V - Plant Material Flow Configuration

Chaos to Order/Clarity to Success

We have had opportunity to work with many clients whose companies had V-Plant Flow. These were Tools (Drills, Taps, end mills, rotary burrs, Washers, Nails), Blow Moulding (Bottles, Cans, Drums, Furniture, Auto Parts), Forgings and a few more.?

The V-Plant is also known as a "one-to-many" plant. This is where a central operation and raw material diverges into different products. Once the materials have passed a divergence point, they usually cannot return to a previous step without major rework. Raw Material count is in 10s and the Finished Good count could be 100s or even 1000s

Major industries that have this flow configuration are -

  1. Steel - Iron Ore to different shapes of finished good - flat, round, cold rolled, hot rolled
  2. Textile - Fibre to Fabric
  3. Garments - Fabric to garments
  4. Refineries - Crude to different end products
  5. Dairy - Milk to dairy products
  6. Basic Agri output - Grains to different food items

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Challenges of V-Plants:

  1. High number of work-in-progress and finished goods compared to raw materials.
  2. Tendency to push for large batches at the first operation, which may not be supported by downstream operations.
  3. Accumulation of slow-moving and non-moving inventory
  4. Long-lead times due to batching and planning runs consideration
  5. Unstable production plan and fire-fighting
  6. Missed deadlines and loss of face for the sales team

We realized that inability to understand and manage V-Plants is a lose-lose situation. The producer, customer, employees and economy as a whole loses big time. It leads to wastage of precious economic resources globally.

Our understanding evolved as we moved from one engagement to other. Now we are quite confident that our recommendations meet the approval of our learned client leaders.

When we started, we felt that we need to inject simplicity. The first na?ve and simplistic attempt was to use the Pareto (80:20) principle as such. We recommended that 20% of the SKUs to be Make to Availability (MTA) and remaining 80% to be Make to Order (MTO). Very soon we found that it was not a practical direction, 20% was too high a number for MTAs and 80% MTO created lot of disturbances in the planning. In a stroke of inspiration we attempted the ratio of 50:40:10 (Head, Body, Tail). We analysed this distribution from multiple parameters for a period of a year - Sales, Throughput, Quantity Numbers, Invoicing Frequency (Count of Invoices), Count of Weeks in which the transactions appeared. We used Excel Pivot Tables to sum up these parameters individually from the invoicing transaction dump. Arranged them in descending order. The top 50% were labelled Head, next 40% as Body and last 10% as Tail. This was done for each criteria. When this analysis was reviewed, we are able to collaboratively develop very elegant solution.

?Hindsight tells us that we were able to do that because of we were standing on the shoulders of giants - Dr Eli Goldratt, Eli Schragenheim , Carol Ptak , Chad Smith and John Maeda (Laws of Simplicity). We were inspired by TOC and DDMRP for creating practical mechanisms of preventing overproduction by strategically choosing buffer locations in Bill of Materials and Distribution Stock Points.

First Law of Simplicity - Reduce.

We ended up with just 8% MTA

Second Law of Simplicity - Organise -

We classified the SKU list into MTA, MTO and new category FTO (Finished to Order). The team had decided to buffer an intermediate divergent point or SFG from where it was possible to carry out the last two finishing operations.

Third Law of Simplicity - Time

The Sales Team had very clear and organised expectations of Lead Time of MTA, FTO and MTO that they could commit to end customers and channel partners. These lead times were significantly shorter than that were experienced earlier

Fourth Law of Simplicity - Learn -

The team learnt that with the constraint of capacity which got exacerbated by frequent set-ups, it was wise and practical to upfront say NO to lot of SKUs in the tail

The final solution:

?MTA - 8%

FTO - 4%

MTO - 23%

NO (Refuse to quote) - 65%


What do you think would be impact of the above decisions? Will a company benefit and create WIN-WIN for all the stakeholders? What would be the impact on Throughput, Inventory and Operating Expense? What would be impact on OEE of the critical machines.

What would be impact on the dilemmas related to variety, inventory, batch-sizes, set-up changes, total volume of business? What would be the customer experience related to lead-time, OTIF?

Converting the above decisions into an Excel based Demand Driven Materials Planning Engine is another exciting experience that my colleagues Ayush Agarwal and CA Aniruddha Joshi have scripted.

Yagna Entrepreneur Success Services Private Limited

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References:

  1. https://www.dbrmfg.co.nz/Production.htm
  2. https://www.planettogether.com/blog/why-you-should-know-the-shape-of-your-plant-vati-analysis
  3. https://www.demanddriveninstitute.com/

Umesh Adoni

Operations Management || Process Excellence

4 个月

When it was refused to quote due to impact of set-up on the constraint capacity, the question that comes to mind is whether the constraint capacity was thereafter utilized fully by alternate products. And 65% are 'refuse to quote' category - Isn't that a large number. Is it by volume??

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Prakash Gadhar

Joint Director- Turning Centre Division, Ace Designers Limited

4 个月

Interesting post . Very curious to know how “NO “ refused to quote was handled both in terms of sales team behaviours and measurements . Most in sales will point to “lost opportunities “or “lost orders.” What’s your view .

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