Manufacturing Operations

1. Capacity planning

   Working out how much the operation can produce, where the limit sits, and whether that matches what has been promised commercially.

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2. Production flow

   How work moves through the operation, and where it waits. Waiting is usually the majority of elapsed time and the cheapest thing to reduce.

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3. Quality management

   Building quality in rather than inspecting it out, with defects caught as close to their source as possible.

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4. Maintenance

   Keeping equipment capable, on a plan rather than on failure. Preventive maintenance is scheduled downtime bought to avoid unscheduled downtime.

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1. Overall equipment effectiveness

   Seiichi Nakajima · 1982

   One number combining how much of the time equipment runs, how fast, and how much of what it makes is good.

   Availability times performance times quality. Multiplying rather than averaging is the design decision that makes it honest: three respectable-looking figures produce a poor one, which is usually a truer description of the line than any of them alone.

   Reach for it when

   When a line is believed to be running well and the output does not agree.

   Where it stops

   It measures the equipment, not the value. A machine can run at high effectiveness producing stock nobody ordered, and the number will approve.

   Seiichi Nakajima, Introduction to TPM, Japan Institute of Plant Maintenance, 1982.

2. Value stream mapping

   Mike Rother & John Shook · 1999

   Draw the whole path a product takes, with the waiting included, and the waiting turns out to be most of it.

   Both material and information flow are drawn on one page, with processing time and elapsed time recorded separately. The ratio between them is the finding: in most processes the time spent actually adding value is a small fraction of the time the thing exists, and nobody believes that until they have drawn it.

   Reach for it when

   Before improving any step, so the effort goes where the time actually is.

   Where it stops

   It is a snapshot of a repeatable flow. Applied to work that varies from case to case it produces a tidy picture of something that never happens twice.

   Mike Rother & John Shook, Learning to See, Lean Enterprise Institute, 1999.

3. Six Sigma and DMAIC

   Developed at Motorola, spread by General Electric · 1986

   Reduce variation until defects are rare, working through a fixed five-step cycle with the measurements agreed up front.

   Define the problem, measure what is actually happening, analyse the causes, improve the process and control it so it does not drift back. The last step is the one that distinguishes it: most improvement efforts stop at improve, and the gain quietly disappears over the following year.

   Reach for it when

   Where a process runs often enough to be measured and the cost of defects is real.

   Where it stops

   It improves processes that already exist and rewards consistency, which is why organisations that push it hardest often become slower to try anything new. It also needs data most small operations do not have.

   Developed at Motorola by Bill Smith from 1986; adopted at General Electric from 1995.

These are other people’s models, named here so you can go to the source and use them properly. The Omnigoal is not affiliated with their authors and is not endorsed by them; nothing of theirs is reproduced here — no canvas, no diagram, no wording. Each is described in our own words, with the originator credited, because the framework is a place to put thinking, not a replacement for the people who did it. Model names and trademarks belong to their respective owners and are used here only to refer to the work itself.

Improving a step that is not the constraint produces inventory, not output. Find the bottleneck before improving anything.