B is for Breakdown, of the equipment variety that is
A research study quoted the figure of machine downtime costing Britain’s manufacturers more than £180bn every year.
This research conducted in partnership with British manufacturers found that downtime – i.e. broken machines and faulty parts hampered productivity.
According to the study, 3% of all working days are lost annually in manufacturing due to faulty machinery, equating to 49 hours of work and £31,000 per company.
I think we can all agree that anything that can be done to reduce downtime caused by breakdowns has to be a good thing.
Preventative planned maintenance is essential for reducing the cost of unplanned downtime. By regularly servicing equipment and addressing potential issues before they escalate, businesses can maintain operational efficiency and avoid expensive repairs and lost productivity.
Predictive maintenance takes a step further by utilising data analytics and monitoring tools to predict when equipment is likely to fail. By analysing patterns and trends in equipment performance, organisations can anticipate issues before they occur, further reducing unplanned downtime.
This proactive approach not only enhances equipment reliability but optimises maintenance schedules, ultimately leading to cost savings and improved operational efficiency.
It just so happens that both these methods of maintenance are available within AIM, helping our clients become more proactive with maintenance and reducing the headaches caused by machine failure.
