Practical guide · Value stream mapping and flow
Production efficiency: what it is, the formula, a worked shift and how to raise it
Short answer
Production efficiency is the output a line actually made, divided by the output it should have made at its standard rate in the same planned time, shown as a percentage. A line that packs 690 cases in a shift with a standard of 750 is running at 92% efficiency.
To calculate production efficiency, multiply the standard rate by the planned production time to get the standard output, divide the actual output by it and multiply by 100. Count only good units if scrap should pull the number down. When a line makes several products, compare standard hours earned with hours worked instead of counting units. Efficiency is not the same as productivity (output per hour of input), OEE (good output against the machine's ideal speed) or utilization (the share of time the line is scheduled). Raise it by measuring where the output was lost and fixing the biggest loss at the bottleneck first.
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What is production efficiency?
On the shop floor, production efficiency compares two counts for the same stretch of time: what the line made, and what it would have made if it had run at its standard rate the whole time it was planned to run. At 100% the line met its standard. Below 100% something took output away: stops, slow running, waiting, scrap. Above 100% the line beat the standard, which more often means the standard is out of date than that the team found a new way to work.
Efficient production, then, means making the planned output with no more time, people and material than the standard allows. The word efficient always needs a yardstick. A plant can measure a line, a cell, a machine, a crew or the whole site against its standard, and each gives a different number. The yardstick is the standard rate, so the number is only as good as the way that rate was set.
Production efficiency in economics
Economists use the term more broadly. A firm or an economy has productive efficiency when it cannot make more of one product without making less of another, which puts it on its production possibility frontier, and when it makes its output at the lowest possible average cost. Allocative efficiency is a separate idea: making the mix of goods that buyers value most. A plant manager's production efficiency is narrower and practical: one ratio, for one line, against one standard, reviewed every shift.
Efficiency and effectiveness
Efficiency asks how little time and material it took to make the output. Effectiveness asks whether the output was the right one: the product the customer ordered, in the quantity needed, on the day promised. A line can run at 105% efficiency on a product that goes straight to the warehouse. That is why efficiency sits beside schedule attainment and on-time delivery on a manufacturing KPI board, never on its own.
The production efficiency formula
Production efficiency (%) = actual output / standard output x 100, where standard output = standard rate x planned production time. Both counts must cover the same time and the same product. If the line ran for 25 days of a 30-day month, compare 25 days of output with 25 days of standard, rather than stretching one figure to fit the other.
The production efficiency formula, worked
Example numbersProduction efficiency = actual output ÷ standard output × 100
Standard output = standard rate × planned production time.
- Planned production time =480 min shift minus 30 min break= 450 min (7.5 h)
- Standard output =100 cases an hour × 7.5 h= 750 cases
- Production efficiency =690 ÷ 750 × 100
| Term | What it means | Where the number comes from |
|---|---|---|
| Actual output | Units the line made in the period | The machine counter, the hour-by-hour board or the shift report. Decide once whether it is all units or good units only, and write it down. |
| Standard rate | Units per hour the line should make with its normal crew and method | A time study of the current method with allowances added, or the engineered rate from the routing. Not last year's average. |
| Planned production time | The time the line was scheduled to make product | Shift length minus planned stops: breaks, the start-of-shift huddle, planned maintenance, no orders. |
| Standard output | What the line should have made in that time | Standard rate x planned production time. |
Unplanned stops stay inside planned production time. Taking them out of the time base before dividing hides them, and the line looks more efficient than it was.
When a line makes several products: standard hours earned
Units of different products cannot be added. A cell that makes a 2-minute part and a 5-minute part has done more work making 40 of the slow part than 40 of the quick one. The fix is to turn output into time: give each unit the standard time it is worth, add those up, and compare the total with the time worked. Production efficiency = standard hours earned / hours worked x 100. Labor reports usually call this labor efficiency, and it is the same ratio as actual over standard output whenever the line makes one product.
| Product | Standard time per unit | Planned units | Units made | Standard minutes earned |
|---|---|---|---|---|
| Bracket A | 2.0 minutes | 150 | 120 | 120 x 2.0 = 240 |
| Housing B | 5.0 minutes | 30 | 40 | 40 x 5.0 = 200 |
| Total | 180 | 160 | 440 |
Efficiency on standard minutes: 440 / 450 = 97.8%. Counting units instead gives 160 / 180 = 88.9%, which marks the cell down for making more of the slow product. Check: the plan is worth 150 x 2.0 + 30 x 5.0 = 300 + 150 = 450 standard minutes, the full shift.
The same table shows why efficiency needs a delivery measure beside it. The cell earned 97.8% of its time, but it made 30 fewer brackets than planned and 10 housings nobody asked for. Schedule attainment, capped at plan for each item, is (120 + 30) / 180 = 83.3%. The manufacturing KPIs guide explains the cap.
Example of production efficiency: one shift on a packing line
This example is illustrative, not from a real plant. A packing line runs one 8-hour shift a day with a crew of five. The shift has a 30-minute break, so planned production time is 450 minutes, or 7.5 hours. The standard rate from the last time study is 100 cases an hour, allowances included. The case packer's ideal cycle time, its fastest steady speed, is 30 seconds a case: 120 cases an hour.
| Count | Value |
|---|---|
| Shift length | 480 minutes |
| Planned stops (break) | 30 minutes |
| Planned production time | 450 minutes (7.5 hours) |
| Stops during planned time (changeover, label jams, waiting for cartons) | 60 minutes |
| Run time | 450 minus 60 = 390 minutes |
| Cases packed | 690 |
| Cases scrapped (crushed or mislabelled) | 15 |
| Good cases | 675 |
| Crew and paid hours | 5 people x 8 hours = 40 labor hours |
Check the cases: 675 good + 15 scrapped = 690 packed.
| Step | Working | Result |
|---|---|---|
| Standard output | 100 cases an hour x 7.5 hours | 750 cases |
| Production efficiency, all cases | 690 / 750 x 100 | 92.0% |
| Production efficiency, good cases only | 675 / 750 x 100 | 90.0% |
| Standard crew hours per case | 5 people / 100 cases an hour | 0.05 |
| Standard hours earned | 690 x 0.05 | 34.5 crew hours |
| Hours worked on the line | 5 people x 7.5 hours | 37.5 crew hours |
| Efficiency on hours | 34.5 / 37.5 x 100 | 92.0% |
Check the other way: 92.0% x 750 = 690 cases, and 90.0% x 750 = 675. The hours form gives the same 92.0% because the line made one product with a fixed crew.
92% looks close to standard, yet the line was stopped for an hour. The reason is the yardstick: the standard rate of 100 cases an hour is well below the machine's ideal 120, so the allowances inside the standard soak up part of the lost time. The next section measures the same shift against the other common yardsticks.
Production efficiency vs productivity vs OEE vs utilization
These words are used as if they meant the same thing. They do not. Each one divides a different pair of numbers and answers a different question, so the same shift scores very differently on each. Here is the packing shift from the example, measured six ways.
| Measure | The question it answers | Formula | The packing shift |
|---|---|---|---|
| Production efficiency | Did the line make what its standard says it should? | Actual output / standard output | 690 / 750 = 92.0% |
| Labor productivity | How much good output came from each hour paid? | Good units / labor hours | 675 / 40 = 16.9 cases per labor hour |
| OEE | How much of the planned time made good product at the machine's ideal speed? | Availability x performance x quality | 86.7% x 88.5% x 97.8% = 75.0% |
| Capacity utilization | How much of what the line could make in its scheduled time did it make? | Actual output / most possible output | 690 / 900 = 76.7% |
| Utilization (time) | How much of the whole day was the line scheduled to run? | Planned production time / calendar time | 450 / 1,440 = 31.3% |
| TEEP | How much of all the hours in the day made good product at ideal speed? | OEE x utilization | 75.0% x 31.25% = 23.4% |
OEE factors: availability 390 / 450 = 86.7%; performance 690 x 0.5 minutes / 390 = 345 / 390 = 88.5%; quality 675 / 690 = 97.8%. Check the short way: 675 x 0.5 / 450 = 337.5 / 450 = 75.0%. Most possible output: 450 minutes at 2 cases a minute = 900. TEEP check: 337.5 / 1,440 = 23.4%.
Why 92% and 75% on the same shift? They use different yardsticks. Efficiency measures against the standard rate of 100 cases an hour; OEE measures against the ideal 120 and counts only good cases. Set the standard rate at the ideal rate and count only good cases over planned production time, and the two become one number: 675 / 900 = 75.0%. So a plant that reports both should say which standard it uses. The OEE calculation guide works OEE through by hand, the OEE calculator does it from shift counts, and the TEEP calculator adds the unscheduled hours.
Productivity is output per unit of input and carries a unit, such as cases per labor hour or tonnes per kilowatt hour. Efficiency is a percentage against a standard. The two can move apart: a plant that buys a faster packer raises productivity at once, but if the standard rate is raised to match, efficiency can fall while the new line beds in. For people rather than machines, the OLE calculator splits labor effectiveness into availability, performance and quality.
Utilization is the one most often read the wrong way. A machine that runs every hour of the day is not a goal in itself: if the orders are not there, running it builds stock, ties up cash and hides problems. Raise utilization only on the step that limits output, and only when the demand is there to use it.
Where production efficiency is lost
Every point of efficiency the line misses went somewhere. On the packing shift, the 450 planned minutes could have made 900 cases at the ideal speed. 675 were good. The other 225 split into four losses: 120 cases that were never made because the line was stopped for 60 minutes, 90 lost to slow running and short stops while it ran, and 15 made and then scrapped. The table lists the usual losses, how each shows up, and the tool to measure or fix it. Seiichi Nakajima grouped the equipment losses into six big losses in Introduction to TPM, the book that also set out OEE.
Where the shift's 900 possible cases went
Example numbers- Good: 675 cases
- Scrapped: 15 cases
- Lost to slow running and short stops: 90 cases
- Not made: line stopped: 120 cases
Of 900 possible cases: 675 good, 15 scrapped, 90 lost to slow running and short stops, 120 never made because the line was stopped for 60 minutes.
| Loss | How it shows up | Measure or fix it with |
|---|---|---|
| Breakdowns | Long stops with a maintenance call on the downtime log | Reducing machine downtime, the MTBF and MTTR calculator and the preventive maintenance guide |
| Changeovers and setups | A gap of output between the last good unit of one product and the first good unit of the next | The SMED changeover calculator and the changeover time post |
| Short stops and slow running | Output below the ideal rate while the line shows as running; OEE performance well under 100% | Micro-stop logging and the six big losses |
| Scrap and rework | Units made that cannot ship first time | The scrap rate calculator, the first pass yield calculator and the scrap and rework guide |
| Waiting for material, people or information | Hours on the board that miss plan with no machine fault | The hour-by-hour production board with a reason for every short hour, and andon to call for help at once |
| An unbalanced line | One station always busy, the others waiting on it | The line balancing calculator, the bottleneck calculator and how many operators a line needs |
| People missing or not yet trained | A slower crew on some shifts, more scrap from one station | The OLE calculator and the skills matrix template |
| No standard method | Each shift does the job its own way, and output depends on who is on | The time study sheet, the standard work sheet and the standard work post |
Check the packing shift: 120 + 90 + 15 + 675 = 900 cases. The 120 is 60 stopped minutes x 2 cases a minute; the 90 is 390 run minutes x 2 = 780 possible, less the 690 packed.
The 6Ms of production are a useful check on the list: most losses sit in the machine, the material or the method, not in how hard people work. A low efficiency number is a reason to go and look at the line, not a score for the crew.
How to improve production efficiency in six steps
Start by measuring, not by buying. A new machine on the wrong step adds cost and no output. These six steps work on one line at a time.
Improving production efficiency in six steps
- 1Time study
Check the standard
- 2
Measure the gap hour by hour
- 3Pareto
Rank the losses
- 4
Work on the constraint first
- 5
Remove the biggest loss
- 6New standard
Hold the gain
Then start again on the next biggest loss
- 1
Check the standard
Time the current method with enough cycles to trust the average (the time study sample size calculator says how many) and add the allowances. A standard the line beats every week cannot show a loss.
- 2
Measure the gap hour by hour
Write the plan and the actual on the hour-by-hour board each hour, with a reason for every hour that misses. A shift total tells you that output was lost; the hours tell you when and why.
- 3
Rank the losses
After two to four weeks, add up the lost minutes by reason with downtime reason codes and draw them with the Pareto chart maker. Put a cost on the top ones with the downtime cost calculator.
- 4
Work on the constraint first
Find the step that limits the line with the bottleneck calculator. An hour gained at the bottleneck is an hour gained for the whole line; an hour gained anywhere else mostly adds stock in front of it, which is the central lesson of The Goal by Eliyahu Goldratt and Jeff Cox.
- 5
Remove the biggest loss with the right tool
SMED for changeovers, preventive maintenance and TPM for breakdowns, error proofing for scrap, line balancing for a station that cannot keep up, standard work for methods that vary by shift. Run each one as a kaizen with a before and after measure.
- 6
Hold the gain
Update the standard work, the standard rate and the target, then review the line's efficiency, OEE and schedule attainment at every shift huddle so a slip is seen the next day.
The kaizen savings calculator turns the minutes and scrap saved into yearly savings and payback, which helps when the fix needs money. For more ideas on what to try once the top loss is known, read the seven ways to improve production efficiency and the plant-wide cost reduction page.
A worked improvement: the same line a month later
Still illustrative. Four weeks of the hour-by-hour board on the packing line show the 60 stopped minutes a shift breaking down as 28 minutes of changeover, 18 of label jams and 14 waiting for cartons. The team runs two kaizens. A SMED workshop moves the film and label preparation outside the changeover and cuts it from 28 to 14 minutes. A two-bin carton supply at the line cuts carton waits from 14 to 2 minutes. Label jams are left for the next round. Stops fall from 60 to 34 minutes a shift; run speed and scrap rate stay the same.
| Measure | Before | After |
|---|---|---|
| Stops during planned time | 60 minutes | 34 minutes (60 minus 14 minus 12) |
| Run time | 390 minutes | 416 minutes |
| Cases packed | 690 | 736 |
| Good cases | 675 | 720 |
| Production efficiency, all cases (standard 750) | 92.0% | 736 / 750 = 98.1% |
| Production efficiency, good cases | 90.0% | 720 / 750 = 96.0% |
| OEE | 75.0% | 720 x 0.5 / 450 = 80.0% |
| Labor productivity | 16.9 cases per labor hour | 720 / 40 = 18.0 cases per labor hour |
Cases packed after: 416 run minutes x 2 cases a minute = 832 possible, at the same performance of 690 / 780 = 88.5%: 832 x 690 / 780 = 736. Good cases at the same quality of 675 / 690: 736 x 675 / 690 = 720. OEE factors after: 416 / 450 = 92.4%, 368 / 416 = 88.5%, 720 / 736 = 97.8%; multiplied, 80.0%.
45 more good cases every shift, with the same crew, the same machine and no overtime. Efficiency against the old standard is now 98.1%, close to the point where the standard stops showing losses. That is the signal to retime the line and decide whether 100 cases an hour is still the right standard, before the label jams are tackled.
Common mistakes when measuring production efficiency
- A standard set from history. If the standard rate is last year's average output, the line runs over 100% whenever it has an ordinary good week, and the losses disappear from view.
- Never updating the standard after an improvement. The line in the example would read 98% for years while a better method was available.
- Dividing by run time instead of planned production time. On the packing shift, 690 cases against 100 an hour for 6.5 run hours reads 690 / 650 = 106%, and the 60 stopped minutes vanish.
- Adding units of different products. Use standard hours earned whenever the products have different standard times.
- Counting bad units as output. Either count good units only, or report first pass yield right beside efficiency.
- Chasing efficiency on every step. Above the bottleneck it builds stock; below it there is nothing to run. Push it at the constraint.
- Averaging percentages across lines. Add up the outputs and the standards first, then divide; the manufacturing KPIs guide works an example.
- Using the number to rank operators. Most of the loss sits in machines, material and methods. Blame teaches people to stop writing reasons on the board.
Tracking production efficiency on the floor
A whiteboard is enough to start. The hour-by-hour production board holds the plan, the actual and the reasons. The OEE tracking sheet logs availability, performance and quality by shift, the six big losses worksheet sorts the lost minutes, and the manufacturing KPI dashboard template trends efficiency week by week with its definition and target. Paper and spreadsheets start to strain when several lines and shifts enter numbers and each short hour needs an owned action that carries from one huddle to the next.
In LeanSuite, efficiency and OEE are set up once as KPIs with a target, Red-Amber-Green ranges and the direction that counts as good, and checklist and form entries from the line appear on the dashboard as soon as they are saved. The short jams that never reach the ERP or MES can be logged as micro-stops and ranked by what they cost, and each loss can be given a cost so the biggest one is clear. See KPI dashboards, micro-stops and loss and cost management.
KPI dashboards
Track production efficiency in LeanSuite
Each KPI is set up once with its target (one for the KPI or a different one per entry), Red-Amber-Green ranges and whether up or down is good.
Go deeper
This page is the short version. These guides cover each part in full.
- How to Improve Production Efficiency: 7 Practical WaysSeven improvement ideas in more depth, from assessing the workplace to building a culture of continuous improvement.
- The Six Big Losses in Lean ManufacturingEach of the six equipment losses behind OEE, with examples and how to cut each one.
- Manufacturing Bottleneck Elimination: 5 Proven StrategiesHow to find the constraint and raise its output before working anywhere else.
- How to Reduce Changeover Time: SMED and Standard WorkThe changeover loss in detail: separating internal and external work and standardising the new method.
- Loss Prioritization Framework for ManufacturingHow to rank losses by cost so the improvement effort goes to the biggest one first.
- How to Improve Shop Floor ProductivityThe productivity side: output per hour and the daily habits that raise it.
All our articles on this subject are in the value stream mapping and flow topic.
Free templates and tools
- Hour-by-hour production boardHourly plan against actual with running totals and the reason for each miss, plus a shift summary by reason.
- OEE tracking sheetOne row per shift for a week. The Excel version works out availability, performance, quality and OEE and charts the week.
- Downtime reason codes template26 starter codes mapped to the six big losses, a log with drop-downs, a Pareto by code and by loss, and a code card for the line.
- Six big losses worksheetWhere a machine's planned time goes: the six big losses in minutes, ranked, with A, P, Q and OEE worked out.
- Time study sheetTime each element over 10 cycles and work out the average, lowest repeatable and standard time. Excel does the sums.
- Standard work sheet templateTakt time, each element's manual, machine and walk time on a time chart, key points and standard WIP.
- SMED changeover worksheetChangeover steps with times, internal or external, what can move, ideas and before/after totals.
- Bottleneck analysis worksheetEffective capacity per station from cycle time, parallel units, availability and yield, the bottleneck, takt and utilization, a queue cross-check and the five focusing steps.
- Skills matrix templatePeople by tasks on a 0 to 4 scale, coverage and gaps per task and shift, and a training plan that closes them.
- Manufacturing KPI dashboard templateWeekly plant numbers in, 14 KPIs out: OEE and its parts, first pass yield, scrap, on-time delivery, recordable rate, cost and absence, each against a target.
- OEE calculatorOverall equipment effectiveness from shift time, downtime, ideal cycle time and part counts.
- TEEP calculatorTotal effective equipment performance: OEE multiplied by how much of all calendar time you plan to run.
- Overall labor effectiveness (OLE) calculatorHow well paid labor hours turn into good output: availability, performance and quality of the crew.
- Downtime cost calculatorWhat an hour, an event and a year of unplanned downtime cost, from lost output, idle labour, scrap and overtime.
- SMED changeover calculatorTime saved by moving changeover steps from internal to external, capacity freed per week and the smaller batch it allows.
- Bottleneck calculatorThe step that limits your line, from each step's cycle time, machines and uptime, with daily capacity and the gap to demand.
- Line balancing calculatorLine efficiency, balance delay and the minimum number of stations from station times and takt.
- Scrap rate calculatorScrap rate, the cost of scrap per period and per year, and what reaching a target rate would save.
- First pass yield (FPY) calculatorFirst pass yield at each step and rolled throughput yield (RTY) across the whole process.
- Time study sample size calculatorHow many cycles of an element to time, from your first readings, with the t formula, the ILO formula and the range method.
- Pareto chart makerPaste categories and counts: sorted bars, cumulative percentage line and the vital few at the 80% line, as a PNG or SVG.
- Kaizen savings calculatorYearly savings, payback in months and first-year ROI of an improvement, from time saved, scrap avoided and its costs.
Key terms
- Overall equipment effectiveness (OEE)
- Total effective equipment performance (TEEP)
- Overall labor effectiveness (OLE)
- Six big losses
- Unplanned downtime
- Planned downtime
- Throughput
- Bottleneck
- Theory of constraints (TOC)
- Single-minute exchange of die (SMED)
- Line balancing
- First pass yield (FPY)
- Scrap rate
Doing this in LeanSuite
KPI Dashboards
Turns raw shop floor data into dashboards anyone can read, so everyone from operators to the plant manager can act on performance.
See KPI DashboardsMicro-stops
Log the brief jams your ERP and MES never report, and see which micro-stops cost the most so you can win back OEE.
See Micro-stopsLoss & Cost Management
Shows where your plant loses money, puts a cost on each loss and gives you the tools to remove it.
See Loss & Cost Management
See it on your own lines
Bring the problem you are working on to a 45-minute demo. Or look around with sample data first, or pilot LeanSuite on your own lines for 90 days, with the setup done by our team.
FAQ
Questions about production efficiency
Production efficiency is the output a line, cell or plant actually made, divided by the output it should have made at its standard rate in the same planned time, shown as a percentage. At 100% the line met its standard; below that, stops, slow running, waiting or scrap took output away.
Multiply the standard rate by the planned production time to get the standard output, then divide the actual output by it and multiply by 100. A line with a standard of 100 units an hour that runs a 7.5-hour planned shift has a standard output of 750. If it makes 690, its production efficiency is 690 / 750 = 92%.
A packing line has a standard of 100 cases an hour and 450 planned minutes in a shift, so its standard output is 750 cases. It packs 690, of which 675 are good. Production efficiency is 690 / 750 = 92% on all cases, or 675 / 750 = 90% counting good cases only.
Productivity measures output per unit of input and carries a unit, such as cases per labor hour. Production efficiency is a percentage: actual output against a standard. A faster machine raises productivity straight away, but if the standard rate is raised to match, efficiency can fall for a while as the new line settles in.
Not usually. Production efficiency compares output with a standard rate that often includes allowances, and may count every unit. OEE compares good output with the machine's ideal speed over the planned production time. On the same shift efficiency can read 92% and OEE 75%. If the standard rate equals the ideal rate and only good units count, the two give the same number.
In economics, productive efficiency means a firm or an economy cannot make more of one good without making less of another, so it sits on its production possibility frontier, and it makes its output at the lowest possible average cost. Allocative efficiency is different: it means producing the mix of goods that buyers value most.
Yes, and when it happens week after week the standard is usually the problem. A standard taken from historical averages, or not updated after an improvement, is easy to beat and stops showing where output is lost. Retime the line and reset the standard rate before reading the number again.
Efficiency asks how much the line made against its standard while it was planned to run. Utilization asks how much of the available time it was planned to run at all, for example 450 of the 1,440 minutes in a day. High utilization is only useful at the step that limits output and when there is demand for what it makes.
Check that the standard rate is current, record output against plan every hour with a reason for each miss, rank the lost minutes with a Pareto chart, and fix the biggest loss at the bottleneck first: SMED for changeovers, maintenance for breakdowns, error proofing for scrap, line balancing for a slow station. Then update the standard work and the standard rate so the gain holds.
Related guides and tools
- How to calculate OEE by hand: the measure that counts only good output at ideal speed
- Manufacturing KPIs: where efficiency sits beside safety, quality, delivery and people
- Reducing machine downtime: a worked month from one downtime log
- How many operators a line needs, from work content and takt time
- Free OEE calculator: availability, performance and quality from shift counts
- Manufacturing cost reduction: turning lost output into money
- Manufacturing KPI dashboard for tracking efficiency by line and shift
More method guides
- The 6 Ms of production
- Poka-yoke
- Model area 90-day plans
- Moving from Excel to one system
- Reducing machine downtime: a worked month
- Andon
- Cycle time vs lead time, worked through
- Root cause analysis
- How many operators a line needs
- Reducing scrap and rework: a worked month
- Unsafe acts and unsafe conditions
- Just culture
- Stop-work authority
- Material review board (MRB)
- Nonconformance and NCRs
- Problem solving methods
- Quad chart
- OEE calculation
- Quality assurance vs quality control
- SOP meaning and format
- Job hazard analysis
- Near miss reporting
- Fishbone diagram
- Pareto chart
- Histogram
- Control chart
- What is a gemba walk
- What is lead time
- What is operational excellence
- How to improve product quality
- Preventive vs predictive maintenance
- Kanban
- FMEA
- PDSA cycle
- Safety moments
- Just-in-time manufacturing
- Kaizen
- 5S
- Total quality management (TQM)
- CAPA (corrective and preventive action)
- Layered process audit (LPA)
- Lean tools
- Lockout tagout (LOTO)
- A3 problem solving
- Preventive maintenance
- APQP
- High reliability organization (HRO)
- Manufacturing KPIs
- Quality metrics
- Practical problem solving
- CMMS
- Risk assessment
- Total productive maintenance (TPM)
- Reliability-centered maintenance (RCM)
Or browse the topics, the full library and the lean glossary.
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