9 September 2024
Efficient operation of machinery and processes is essential to meet production targets and maintain quality and profitability within a manufacturing company, whether this is in food processing plants, on machinery manufacturing lines or automotive assembly lines.
Unfortunately, equipment breakdowns do happen, machines stop, and supply chains are disrupted, resulting in a knock-on effect to the rest of the business. Unplanned downtime is more than just an inconvenience. The high costs of downtime can quickly have a catastrophic impact on your company’s bottom line and reputation. How much is your company losing when operations grind to a halt?
When we investigated how much unplanned downtime was costing businesses globally, we, like many companies we have discussed this issue with, were staggered by the numbers reported.
According to the 2022 True Cost of Downtime survey, globally, annual downtime losses for Fortune Global 500 firms totalled $1.5 trillion. This is a 65% rise in two years and constitutes 11% of these firms’ turnover. $2 million per hour is the cost of downtime in an automotive plant – up from $1.3 million in 2019-2020. Next to a safety or environmental mishap, unplanned downtime represents one of the costliest events a manufacturing or industrial plant can experience.
Is there a solution to this and what exactly is causing this catastrophic issue to occur so prominently across the industry?
The average manufacturing facility suffers 20 downtime incidents a month, with the average large plant losing 25 hours a month to unplanned downtime – more than a full day’s production, so if you’re encountering downtime, you’re not alone!
One of the reasons for this is businesses using and relying on inefficient reactive, run-to-fail maintenance processes. Meaning, actions are only taken, and repairs are only done once the equipment has already broken down.
Inefficient maintenance processes can result in a series of negative events, such as:
· Poor real-time operations visibility
· Additional maintenance costs
· Being unable to obtain or locate spare parts at the point of need
· Increased wage bill through wasted wrench time
· Having to rely on outdated paper-based systems
· Lost orders/work backlogs.
With human error and supply chain disruptions also contributing, these issues can lead to immediate production halts which set off a ripple effect of inefficiencies and delays. One machine breakdown can disrupt an entire production line, leading to increased labour costs, delayed orders and poor customer relationships.
With inflation spiralling and production costs higher than ever, resulting in each hour of unplanned downtime now costing at least 50% more today than it did in 2019, more and more businesses are subsequently searching for solutions.
The first step to tackling downtime is to identify where issues are occurring through tracking and monitoring of events. Businesses can then form a clearer picture of how to improve their operations.
Secondly, many businesses are now engaging with innovative strategies and digital transformation to fundamentally change the way they operate and deliver, especially with the rise of The Internet of Things (IoT) which enables devices and software to generate substantial data on machinery performance. Utilising this, there are many ways to help combat downtime for example, through preventative maintenance, condition monitoring, predictive maintenance and employee training.
Preventative maintenance helps prevent future unexpected failures by performing regularly scheduled maintenance activities to ensure machinery is maintained/fixed before it fails. It can include a range of activities and general tasks for engineers to complete, such as servicing of components, repairing and replacing parts, and ensuring other systems such as electrical, are in good working order and comply to standards.
Machine condition monitoring is an approach which allows you to assess and predict the health of a machine over a period of time. This is done through using a combination of monitoring software and machine sensor data to measure vibration and other parameters in real-time.
Predictive maintenance combines strategic foresight with advanced technology to pre-empt equipment failures and halts in production. It uses data analytics and machine learning to predict when maintenance should occur before problems start to arise, in turn reducing downtime and extending equipment life.
Human error can play a part in downtime, especially if employees have knowledge gaps. When staff are improperly trained, they can make mistakes, such as when operating machinery or installing parts. This then results in expensive corrections having to be made.
Investing in employee training ensures that workplace procedures are followed to spec. By using a software system like invisu, employees can access interactive learning and testing with walkarounds of the working environment that will show them precisely how to install parts correctly. It also enables specialist knowledge to be shared with the next generation of engineers and improves employee engagement and morale.
Invisu is currently assisting manufacturing companies across the UK and globally to manage their entire lifecycle of equipment from assembly through to decommissioning. Our software ensures equipment is correctly and consistently maintained by helping to prevent unplanned downtime before it occurs and provide rapid intervention at the point of need upon the occurrence of production stoppages.
If your company is suffering downtime and you’re unsure where to start, please get in touch. Our team can visit your site on a consultancy basis to evaluate where issues are occurring, where improvements can be made, and advise on the best solutions available to keep your facility running at maximum capacity.