The Six Big Losses concept was developed by Seiichi Nakajima in 1971 to identify and categorize sources of productivity loss from an equipment perspective in manufacturing businesses. The six categories of loss are: 1) equipment failure, 2) set-up and adjustment, 3) speed loss, 4) minor stoppages and idling, 5) defects and rework, and 6) start-up and yield loss. Identifying these specific sources of loss allows companies to take preventative actions to solve equipment problems, improve productivity, and minimize unplanned downtime.

1. The Six Big Losses
Prashant Uttarkar
The Six Big Losses concept came from TPM creator Seiichi
Nakajima. He developed it during his time in Japan’s Institute
of Plant Maintenance in 1971. It was created to identify and
categorize how a business encounters productivity loss from
the perspective of the equipment that the company uses.
The Six Big Losses are a continuation of TPM. It work hand
to hand with OEE, OEE factor (Availability, Performance, and
Quality) should be broken down further to provide more
granular data. It help to categorize the losses that pertain to
pieces of equipment losses. It assist to take preventative action
to solve equipment problem effectively and improving
productivity loss from an equipment perspective. According
to Nakajima in the study of Alvira et al activities and actions
undertaken not only focus on preventing damage to the
machine / equipment and minimizing machine / equipment
downtime.
1. Equipment failure (breakdown) loss: The largest of all
losses, it includes significant periods of time equipment
is scheduled for production but is not running due to
unplanned events such as tool failures, unplanned
maintenance, upstream / downstream blockages, etc.
2. Set-up and adjustment loss: Losses due to (planned)
downtime from changeover and minor process
adjustments.
3. Speed loss: When equipment runs slower than the ideal
cycle time due to poor conditions, operator inexperience,
inadequate lubrication, etc.
4. Minor stoppage and idling loss: Small stops that
account for short periods of time when the equipment is
not running in order to address things like clearing a jam,
changing a setting or hanging a part. Small stops are
typically remedied by the operator within a few minutes.
5. Defect and rework loss: This loss accounts for the
production of defective parts that are scrapped or that
require rework. These losses typically occur during
steady-state production and are caused by operator error,
equipment handling, or incorrect equipment settings.
6. Start-up / Yield loss: Losses that occur during equipment
warm-up, or after a restart post changeover before the
machine has reached stable production.
Six Big Losses will:
 Help you more accurately identify the causes of
production loss;
 Give you the information required to make the right
decisions; and
 Allow you to increase production time with minimal
impact on quality.
Conclusion:
Identification of the Six Big Losses is one of several lean tools
used by manufacturers today to understand the most universal
forms of waste within manufacturing operations. In addition
to other tools, such as root cause analysis, 5S, and JIT
production, detection of the Six Big Losses will streamline
production and expose bottlenecks that are costing
manufacturer’s unnecessary cash.
Reference:
1. Six Big Losses: Important Concepts to Always Bear in
Mind.
2. Why the Six Big Losses are crucial to your preventative
maintenance regime, Peter Thompson , 25 January 2018.
3. Overall Equipment Effectiveness Improvement on
Cutting Machine by Minimizing Six Big Losses
Rosalendro Eddy Nugroho1*, Syifa Khoirudin.
4. OEE - The Six Major Losses And How They Affect
Equipment Effectiveness, , Alejandro Sibaja at May 17.
5. 6 Big Losses in Equipment Efficiency by Kaufman
Global.
6. Lean Manufacturing Tools: Identification of the Six Big
Losses. Estes design and manufacturing. Inc. www
7. Six Big Losses Approach and Kaizen Philosophy
Implementation to Improve Overall Equipment
Effectivenes (OEE), (Case Study: PT. ABC, Areinforced
Steel Manufacturer) Untung Mardono, Doto, Anni
Rohimah, Erry Rimawan Magister Industrial
Engineering, Mercu Buana University.