Downtime Reduction: A Critical KPI for Operational Excellence

Manufacturers and producers can operate the most effective processes and workflows, but when downtime strikes, it can put the leanest of operations out of kilter. In an age of predictive maintenance and great efficiencies in planned (and speedy) maintenance, tracking and dealing with unplanned outages or downtime is a vital part of mitigation and management.

Unplanned downtime for manufacturers can wreak havoc across the production floor and your supply chain. Typically caused by machinery malfunctions, control software errors, spillages or human error, when a machine or person triggers the red “stop” button, the costs can be huge.

The impacts rumble on beyond the balance sheet, through productivity metrics redlining and the potential of lost orders or reduced customer satisfaction.

The Role of KPIs in Operational Excellence

To stay on top of the impact and cost of downtime in manufacturing, its effects must be measured as key performance indicators (KPIs), something many firms still avoid doing. Time, cost, knock-on delays, additional assets required and so on must all be tracked.

The standard KPIs for manufacturing related to downtime incidents include:

• Mean Time to Repair (MTTR), to fix the problem

• Mean Time to Recover, for normal operations to resume

• The Mean Time Between Failure (MTBF), the gap between repeated outages or downtime

Measuring these metrics used to be complex, but with modern business apps and dashboards, they are tracked live, with status updates keeping all stakeholders and operators involved to provide an accurate guide to the resumption of normal service.

Aiming for Operational Excellence

Sometimes it can take a major downtime incident to drive a manufacturer’s leadership to change their reactive approach to operations. At this point, the typical call is to update programs and processes to aim for operational excellence.

With a handle on the cost of downtime, and visibility into the most efficient way to resolve an issue, businesses can then look to improve their operations overall. They can also learn lessons and avoid issues that might appear elsewhere.

For businesses looking to achieve operational excellence, measuring every aspect of operations is vital. Aligning those KPIs to business goals, and ensuring that all managers and workers are informed as to why processes change, and the new ways of using measuring and reporting tools are critical.

Using training and tracking to ensure compliance and appropriate use of new metrics, the business can better track the adoption of new production or manufacturing processes. And their beneficial impact on operations.

If the changes are not beneficial, they can review them to find weaknesses in assumptions or gaps between predictions and reality. One method of avoiding those gaps is the use of digital twins, a virtual recreation of a production system, supply chain or other process.

Used as part of efficient production methods, be they optimised logistics, lean processes, advanced manufacturing systems, managers can view the cost of downtime.

How KPIs Drive Process and Performance Improvement

With all the parts in place, the business will be better aware of the impact of downtime, it has the processes to resolve a problem faster, and workarounds to minimise any impact.

The production floor is also best placed to reduce downtime by using preventive maintenance and proactive scheduling, ongoing training to keep staff up-to-date with new technologies and processes, and considering the latest and future technology adoption as digital factories and supply chains become the norm.

However, all businesses should note that increased use of IT puts their manufacturing processes at risk from hackers and other criminal activity, including state-sponsored sabotage. IBM notes that manufacturing is a prime target, so all firms should build-up resilient and protected IT services that can defend against such attacks.

While many businesses and shop floors are reluctant to change, demonstrating how the classic examples (Toyota, Volkswagen’s Wolfsburg factory) shape modern production and supply chains is one way to win over doubters. Another idea is to get workers on board by adopting their suggestions based on experience to help drive performance improvement changes forward.

Through a mix of knowledge, technology adoption and the use of smart software, with AI capable of refining the values of predictive maintenance, any manufacturing business can drive the organisation forward through operational excellence initiatives to avoid the kind of crippling downtime that can seriously damage a business.

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