Steve Beeler

You have a goal…I have a way to get you there.

Constraint

Business Case for Manufacturing Plan Verification

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An ounce of prevention is worth a pound of cure. Everyone knows and accepts this adage but in today’s lean global economy, not everyone has the people and the budget to walk the talk. Quantifying the answers to these questions will build the business case for manufacturing plan verification.

The Business Case for Manufacturing Plan Verification

(1) What is the value of minimizing the seven wastes (over-production, inventory, motion, over-processing, waiting, correction, and conveyance?
o operating costs
o investment

(2) What is the value of reducing the risk of capacity shortfalls found after a new production line or business process is launched?
o lost sales
o overtime
o overmanning
o post launch trouble shooting and additional investment

(3) What is the value of predicting operational and financial metrics prior to launching a new manufacturing or business process?
o direct / indirect labor utilization
o overall equipment effectiveness (OEE)
o dock-to-dock time
o work-in-process inventory
o finished product inventory
o build-to-schedule
o total contribution margin
o cash flow
o profits
o return on investment

(4) What is the value of verifying operating plans prior to launching a new manufacturing or business process?
o direct labor
o indirect labor
o shift hours
o quality control plans
o preventive maintenance plans
o mix / sequence flexibility
o batch sizes / changeovers
o scheduling and sequencing algorithms

(5) What is the value of actively managing the constraint during the planning of a new manufacturing or business process?
o flexibility
o expansion

The answers to these questions will likely roll up into a pretty big $$$ number. With today’s commercially available discrete event simulation software, the business case for manufacturing plan verification is therefore quite strong.

The world is full of uncertainty and change. Robust manufacturing plans will stack the odds in your favor. Simulate first to drive business plan targets down to each cell. Then simulate again to verify that the system works. An ounce of prevention is worth a pound of cure. In a nutshell, that is the business case for manufacturing plan verification.

 

Best Constraint Location

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In my previous blog on Theory of Constraints, I defined the constraint (aka, the bottleneck) as the weak link in the chain. Every system has one. If there is a choice, where is the best constraint location?

Best Constraint Location

The Ugly. By far the worst place to have the constraint is in the marketplace. When the constraint is outside the four walls of a company’s operations, management’s control over it is very limited. Operational and financial performance is completely exposed to market turbulence: product and pricing actions by competitors, shifts in aggregate demand, changes in consumer tastes, and so on.

In a perfect world, annual demand will exceed capacity by one unit per year. Why? Operational and financial performance can be optimized by managing the internal constraint while having only one unhappy customer.

The Bad. An internal constraint should not be in a process that is unreliable, uncertain, or inflexible. The constraint is the “drum” that establishes the rhythm for the enterprise. If the constraint does not have a steady beat, then wastes of all types (especially inventory and waiting) will be incurred at non-constraints as they struggle to keep in step with the constraint.

Processes with low availability and/or low process capability are also bad places for the constraint. The opportunity costs of production losses and scrap at the constraint are huge.

An inflexible constraint is another bad idea. The entire organization will suffer if its constraint cannot quickly respond to shifts in consumer tastes or aggregate demand. Adding cost at the constraint (e.g., overtime, outsourcing, etc) to capture incremental profits is good business. Watching a more nimble competitor grab those dollars is not.

Best Constraint Location

The Good. A good constraint is inside the four walls of your operations and is reliable, certain, and flexible. Easy to say, harder to do.

Choose a familiar technology…the constraint is no place for a steep learning curve. Minimize planned maintenance during shift hours. Cross-train employees for “instant” capacity at the constraint. Design the constraint to be flexible across a broad range of mix and sequence scenarios. Adequately buffer the constraint upstream and downstream to minimize block and starve waiting losses.

At the constraint, all the little details matter.

5-Step Throughput Improvement Model

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In my previous blog, I used the “ten machine” manufacturing puzzle to establish the need to think systemically: in isolation each machine hit its performance target, in combination the system failed to reach its goal. The 5-Step Throughput Improvement Model is a proven process to solve this local optimization paradox.

5-Step Throughput Improvement Model

Theory of Constraints views an organization as a chain of dependent activities or functions all working towards a goal. The constraint is the weakest link in the chain…the link that most severely limits the organization’s ability to achieve higher performance (throughput) relative to goal. In business, that goal is usually to make more money now and in the future. The following five step process will continuously improve performance (increase throughput) to the goal.

5-Step Throughput Improvement Model

Step 0: Define the system. In this context, the “system” includes both the goal and the activities and functions that deliver the goal: Who and what contributes to making money?

Step 1: Identify the system’s constraint. Finding the constraint in a large, complex organization can be a challenge. A simple rule of thumb: If a link in the chain is blocked then the constraint is downstream. If a link is starved then the constraint is upstream. More on finding the constraint in subsequent blogs.

Step 2: Decide how to exploit the constraint. How can we get the most out of the constraint: Approve overtime? Reduce set up times? Improve scheduling? Increase in-coming inspection?

Step 3: Subordinate everything else to the decisions made in Step 2. What can non-constraints do to ensure that the constraint is as productive as possible: Cross-train people? Improve quality? Take lunch and breaks at different times?

Step 4: Elevate the system’s constraint. Add capacity if and only if the constraint’s performance has been truly maximized.

Step 5: If a constraint is broken in Step 4, go back to Step 1. Repeat process on the next constraint until the organization’s goal has been met. If the goal is open ended (make more money!), then this process never ends.

The late Dr. Eliyahu Goldratt has a series of books on Theory of Constraints. His first book, The Goal, applies TOC to a manufacturing plant. A later book, Its Not Luck, applies TOC to a conglomerate’s portfolio of businesses. Both books are novels, not textbooks, and they are very easy reads. I highly recommend them.

Terminology

Bottleneck = same as constraint