What are the Six Big Losses in manufacturing and how to eliminate them

Mila Budeva
Mila Budeva
Feb 13, 2018

Developed in 1971 at the Japanese Institute of Plant Maintenance, the Six Big Losses in manufacturing have been used as a way to categorize equipment-based losses and maximize overall equipment effectiveness. The six big losses can be split into three general categories- Availability, Performance and Quality losses. Let's look at what they are in more detail and how digital capabilities can help to minimize them for greater effectiveness and efficiency on the shop floor.



Availability losses

1. Equipment failure

The first big loss is caused by equipment, which is not running despite being scheduled for production, resulting in unplanned downtime. This can be due to machine breakdowns, tooling failure or emergency maintenance stops.


2. Setup and adjustments

The second big loss is also caused by downtime when equipment is not running due to a changeover, machine and tooling adjustments or a planned maintenance as well as setup time and quality inspections. 


So how can technology help to minimise availability losses?

Capabilities such as mobiles, wearables and IoT conneced devices can help to improve visibility, operational compliance and productivity on the shop floor. When integrated in a single platform, they can enable manufacturers to monitor, measure and improve operational standards on the shop floor in real time.

With availability losses,  IoT connected devices can help to implement pre-emptive rather than post-hoc maintenance, helping to minimise downtime and improve the effectiveness of changeovers and adjustments. For example, a temperature sensor can send alerts to operators' mobile or wearable devices when the machine approaches peak temperature which will result in its shut-down so operators can pre-emptively respond to the danger of overheating.

In the instance of changeover - the process of converting a tool or a machine from running one product to another - downtime is often caused by workers not being aware of it in time to prepare the right tools and materials or of what the target time for the changeover is. Pushing a reminder to workers' mobiles or wearables about the upcoming changeover as well as step-by-step guidance on how to perform it can help to reduce downtime. Gamifying the process and rewarding workers points for completing the changeover within or below the target time can help to further boost efficiency.


Performance losses

3. Idling and minor stops

Also known as small stops, idling and minor stops account for short periods of time when the equipment stops operating. They can be caused by material jams, product flow obstructions, wrong settings or cleaning. These issues do not normally require maintenance personnel and can be resolved by the operator in a couple of minutes. As such minor stop do not individually result in significant downtime, they hold the risk of becoming a normalised part of the production process, overall reducing effectiveness and efficiency.


4. Reduced speed

In this case, equipment runs more slowly than the Ideal Cycle Time - the estimated minimal time required to produce a part. Reduced speed can be due to poorly maintained or slow equipment, substandard materials that damage the equipment or inexperienced operators running the equipment.


Technology can help address performance losses by helping to improve training and provide operators with the relevant information at the point of action. For example, management can create a step-by-step video on how to set up the window frame machine that the operator can refer to on her tablet before or during the setup. She can then take a picture of the machine as evidence of complying with the standard operating procedure (SOP).


Quality losses

5. Process defects


6. Reduced yield

Both quality losses account for the production of defective parts, including scrapped parts and parts that can be re-worked. Process defects occur during steady-state production and are commonly caused  by wrong equipment settings, operator errors, poor equipment handling as well as expiration. Reduced yield accounts for the defective parts produced in the warm-up stage of production. It is caused by poorly executed changeovers, wrong settings, or equipment generating waste after startup.


Technology can help management to gain real-time visibility over quality losses. Analysing data captured on the shop floor can help to identify the root causes and communicate witht the workers the required corrective actions. Data on the majoriry of process defects being caused by operator error, for example, can suggest the need for updating SOPs. 


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