Are maintenance issues affecting manufacturing productivity?
Did you know that reactive maintenance can cost 10x more than preventative and predictive maintenance? Budget and time constraints often see maintenance programmes pushed to the bottom of the priority list. This can be a false economy, leading to ‘firefighting’ and an expensive, urgent fix of a broken machine which has caused production to grind to a halt.
A focus on meeting production targets and delivery deadlines often mean production departments are reluctant to schedule ‘non-production’ maintenance timeslots. But regular, monitored equipment shutdowns are the route to long-term productivity. Measuring and improving machine uptime and performance ensures manufacturers have vital data for improving productivity and monitoring trends. This data is critical in enabling companies to extend mean time between failure (MTBF) rates and improve equipment reliability.
Savvy manufacturers monitor the condition and performance of equipment regularly – before it begins to affect productivity.
7 reasons why you should optimise your maintenance programme:
- Reduce operating costs
- Increase on-time delivery
- Extend the useful life of equipment
- Increase capacity
- Decrease lead-time
- Improve product quality
- Reduce scrap
Where to start? 3 steps to more effective maintenance:
1) Create processes to promote reliability
Without accurate data on equipment availability and performance, it’s impossible to implement relevant processes to maximise uptime.
2) Work smarter, not harder
Avoid a skills gap when staff move on, taking valuable knowledge with them. Companies need to build documented skill sets to transfer this knowledge to new workers.
3) Utilise systems and standards
How can companies implement a shift from ‘react mode’ to preventative and predictive maintenance? Implementing systems to support and standardise the points above ensures that proactive steps are taken early, and ‘react’ mode is avoided.
Maintenance management inevitably requires an upfront investment of effort and resources without necessarily yielding short term results. Some initial areas to focus on include cleaning and lubrication, autonomous maintenance, training operators on relevant work standards etc. Operators are the first line of defence in any predictive maintenance programme.
Data collection processes have improved markedly in recent years, with low-cost smart devices enabling real-time failure predictions using e.g. temperature, run times and vibrations data from sensors. Previously, highly skilled technicians were needed to assess performance and predicted failures based on ad hoc data, typically collated on an irregular basis when time allowed. Manufacturers can now benefit from real-time analysis with a visual display of collated data, enabling cost-effective, simplified maintenance management. Decisions on repair/replacement of equipment can be taken with the full facts to hand – ensuring maximum uptime of critical equipment and proactively managing potential issues.
In summary, any manufacturing facility will undoubtedly still encounter both planned and unplanned downtime, but advanced maintenance management processes and utilisation of the latest technology for data collection and analysis ensure that the financial impacts on the business are kept to a minimum and productivity is maximised.
Review the latest webinar Maximise Productivity Through More Effective Maintenance from our partner Parsec™ Corp for information on how to use effective maintenance management techniques to improve OEE, reduce downtime and decrease production losses. Watch the recording here https://attendee.gotowebinar.com/recording/4420719945226646785