Part of the Total Productive Maintenance (TPM) methodology invented by Seiichi Nakajima in the 1960s, Six Big Losses is a practical tool that can help identify inefficiencies in production.

The approach focuses on losses, highlighting the idea that equipment-based flaws in the production workflow directly harm the bottom line of a manufacturing business.

The Six Big Losses correspond to another well-known term coined by Nakajima – Overall Equipment Efficiency (OEE).

The link between these two concepts is clear – deal with the six losses, and you’ll improve the OEE of your operation as a result.

 

The Six Big Losses Vs. OEE
The Six Big Losses directly correlate to the components of OEE.

 

The Six Big Losses in Lean Manufacturing

Here is a general outline of the Six Big Losses along with a few examples and an explanation of how industry 4.0 reduces the impact of each loss type:

AVAILABILITY LOSS

1. Unplanned Stops

Stops that last a considerable amount of time during which equipment is scheduled to be running, but has stopped unexpectedly.

Examples: equipment breakdowns, tool failures, unscheduled maintenance, lack of raw materials, limited workforce.

How industry 4.0 helps: This type of stop is best dealt with through prevention since once downtime hits, there isn’t much operators can do to resolve the problem.

The first step is to accurately map the issues causing these stops. Collect and aggregate your data from SCADA, MES, and historians. Then, employ industrial AI in the form of machine learning for precise anomaly and pattern detection.

This will provide the knowledge necessary to eliminate the root causes of recurring stops of this kind.

2. Planned Stops

Stops in which machinery is scheduled for production, but has ceased to run due to a planned stoppage.

Planned stops are also defined as the time between the production of the last product from the previous run and the first product of the new run.

Examples: tool adjustments, raw materials changes, planned maintenance, quality inspections, scheduled breaks, and meetings.

How industry 4.0 helps: Industry 4.0 offers predictive maintenance as an optimal solution for Planned Stops. Unlike preventive maintenance that leads to too many Planned Stops, predictive maintenance plans stops that aren’t too late, or too early, but “just in time”.

Parts aren’t switched out too early, and production doesn’t have to be stopped for unnecessary maintenance checks.

When stops are necessary, cleaning, filling, and maintenance should be orchestrated to take place within the same stoppage window.

 

PERFORMANCE LOSS

3. Small Stops

Stops in which machinery ceases to run for 1-2 minutes because of a problem that is typically resolved by the operator.

Small Stops are often recurring problems, resulting in a certain indifference among operators who may not realize the cumulative impact of these disruptions.

Examples: blocked or misaligned sensors, raw material jams, misfeeding, incorrect configuration, minor cleaning activities.

How industry 4.0 helps: Reducing small stops is achieved through automated root cause analysis and by changing the work practice of operators.

The first step is to document these minor stops, recording and categorizing sensor information and other related data. This will give operators a stronger sense of accountability while providing actionable insights into the root causes of this type of loss.

Through machine learning, these insights become predictive, allowing malfunctions of this type to be prevented completely, or at the least, well-prepared for.

4. Reduced Speed

When equipment runs slower than the optimal cycle time (the least amount of time required to manufacture one item/volume unit.)

Examples: lack of operators’ experience, worn-out equipment, low quality raw materials or lubricants, problematic environmental conditions.

How industry 4.0 helps: Issues of reduced speed are actually combated as a byproduct of dealing with the other Big Losses, whether availability, performance, or quality-related.

For example, automated root cause analysis can point to inefficiencies that were previously undetected such as lubricant issues. While the lubricant quality may have led to a mechanical problem, it’s likely that addressing it will also improve cycle times.

Other directions for dealing with Reduced Speed are to:

  • Identify bottlenecks and other inefficiencies.
  • Where possible, automate tasks that until now have been manual.
  • Provide operators with better training – they hold the most power when it comes to reducing the impact of this particular loss.
Using industry 4.0 technologies to reduce the impact Big Losses such as Unplanned Stops and Production Defects mitigates instances of Reduced Speed automatically.
Using industry 4.0 technologies to reduce the impact of big losses such as Unplanned Stops and Production Defects mitigates instances of Reduced Speed automatically.

 

QUALITY LOSS

5. Production Defects

Defective products manufactured while production is generally stable.
In this case, defects include scrapped parts along with those that can be reworked. This is because OEE measures quality according to First Pass Yield (FPY), making this Big Loss a quality criterion.

Examples: incorrect operation of equipment, poor setup.

How industry 4.0 helps: Applying predictive analytics to data collected from sensors and cameras will determine whether anomalies are likely to lead to critical quality deviations. In this way, timely adjustments to production can be made to prevent drops in quality, and the resultant waste of raw materials.

6. Startup Defects

Defects produced during the startup phase, before the normal production cycle is reached.

Examples: machinery requiring a number of warm-up cycles, defects due to planned maintenance, poor changeover execution.

How industry 4.0 helps: Changeovers often place operators in a position of blind guessing when setting up a machine for a new batch.

With industry 4.0, the current status of all equipment is accurately measured, stored, and analyzed at all times. Operators can configure the line for a new batch without having to guesstimate settings. This cuts down defects and reduces the wastage of raw materials.

 

Benefits of using the Six Big Losses in TPM

Utilizing the Six Big Losses leads to the following benefits:

  • Accurate identification of the root causes of lost production time
  • Crucial insight to inform better optimization decisions
  • Increased production time without compromising on product quality.

The Six Big Losses is a strategic methodology that can be used to guide ongoing improvements in production.

Part of the strength of this approach is the idea that even minor inefficiencies add up and hurt the OEE.

Industry 4.0 use cases such as predictive maintenance and automated RCA significantly cut down the impact of the Big Losses, leading to lower production costs and improved profitability.

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