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Manufacturing KPI dashboard template
A manufacturing KPI dashboard shows a small set of key performance indicators for a plant or area against targets, so the team can see where to act this week. This template takes one row of plant numbers a week for 13 weeks: hours worked, recordable cases and near misses, units good first time, reworked and scrapped, units scheduled, order lines due and delivered on time, planned production time and the stops inside it, and the total cost of the week. From those it works out 14 KPIs in six areas (safety, quality, delivery, equipment, cost and people) and colors each one green, amber or red against a target and an amber band that you set. Page 1 is the dashboard grid for 13 weeks, page 2 is the weekly numbers sheet and page 3 has the formula of every KPI and a worked example. The Excel version adds the latest week, the last 4 weeks, the 4 weeks before and all weeks, a trend, four 13-week charts and a one-page print. Each KPI is a plain ratio, and the 4-week and 13-week figures are ratios of sums, not averages of weekly percentages. The formulas for first pass yield, scrap, rework, performance and OEE follow a published restatement of the ISO 22400 KPIs by Kang, Zhao, Li and Horst (2016); the recordable rate follows the US Bureau of Labor Statistics incidence rate formula; the rest are common practice. We could not read ISO 22400-2 itself, which is paywalled, so nothing is quoted from it. Targets and amber bands are example values, not benchmarks.
Free to use: print it, copy it and edit it for your team. Enter your name and work email once to download.
When to use it
When to use a manufacturing KPI dashboard
- For the weekly review of a plant or area, when the numbers now come from five different sheets and nobody trusts the totals.
- To build the numbers for a tier board or a daily huddle from raw counts, with one definition for each KPI.
- Before buying dashboard software, to learn which numbers you need, how each is defined and who enters them.
- When a customer or corporate team asks for OEE, first pass yield and on-time delivery and you need one way to work them out.
How to fill it in
- 1
Pick the plant or area and the week
One plant or one area per workbook, with weeks that start on the same day. Type the date the first week starts and the weeks fill in from there.
- 2
Enter every number every week
Seventeen numbers a week. A blank means not recorded, so fill in a zero when the real figure is zero. Hours worked leave out paid time not worked, such as vacation, sick leave and holidays.
- 3
Set the direction, target and amber band
For each KPI say whether higher or lower is better, the target, and how far from the target still counts as amber. Set them from your own history and your customers' needs. The example values on the Example dashboard are not benchmarks.
- 4
Read the status, then the trend
The status colors the latest week. Look next at the last 4 weeks and at the trend against the 4 weeks before: one bad week is a question, four are a pattern.
- 5
Act on the reds and ambers
Give each red or amber an owner and a date, and write them on page 1. The dashboard says where to look. It does not say why.
- 6
Keep the definitions fixed
Write down what each KPI counts and do not change it mid-year. A KPI that changes meaning cannot be trended.
A filled-in example
Illustrative, not a benchmarkAn example: an example plant with six assembly lines on two shifts, 13 weeks of numbers, 14 KPIs (illustrative numbers). The targets and amber bands are example values.
- OEE rose from 61.3% in week 1 to 68.0% in week 13: availability from 82.0% to 86.0%, performance from 80.0% to 84.0% and first pass yield from 93.5% to 94.1%. OEE is availability x performance x first pass yield.
- On-time delivery fell from 94.9% in week 7 to 87.0% in week 8 and 84.2% in week 9 (369 of 424 order lines on time, then 363 of 431), and was back to 95.1% in week 13.
- In weeks 8 and 9 the schedule rose from 34,140 to 35,520 units while good output fell from 32,499 to 32,147, so schedule attainment dropped to 90.5% and 89.5%.
- The recordable incident rate is 3.85 for all 13 weeks: one case in week 4 over 51,980 hours worked, × 200,000. At week 4 the same case gave 12.54, which is why the rate is a weeks-to-date figure.
- At week 13 the dashboard shows 7 KPIs green, 6 amber and 1 red: rework at 4.3% against a target of 3.0% with an amber band of 1.0%.
The dashboard does not say why delivery fell. It shows which weeks to look at and what moved with it: the plan went up and output did not. By week 13 on-time delivery was back to 95.1% and OEE had gained 6.7 points.
Common mistakes
Changing a definition half way through
If OEE counts planned time one way in March and another way in June, the trend means nothing. Write each definition down, with what it includes, and keep it.
Averaging weekly percentages
The average of four weekly first pass yields is not the first pass yield of the four weeks. Add the units first, then divide. The workbook's 4-week and 13-week figures are worked out this way.
Judging safety by one week's rate
One recordable case in one week gives a rate far above any target, and no case gives zero. Use weeks to date and the 4-week figure, and look at near misses reported as well.
Copying someone else's target
A target from another plant or a web page does not tell you what your customers need or your lines can do. Start from your own last 13 weeks and write what the target is for.
Download the template
Free to use: print it, copy it and edit it for your team. Enter your name and work email once to download.
Run this template in LeanSuite
LeanSuite's KPI dashboards track every KPI against its target, with red, amber and green ranges, KPI trees and live huddle boards, so operators and the plant manager act on the same numbers.
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Manufacturing KPI dashboard template: common questions
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A shift handover sheet, a red tag log, a changeover checklist for one machine: if your team uses it on the floor, ask.