Machine downtime refers to manufacturing periods where a machine is unavailable for production for one reason or another. To maintain optimal levels of productivity, profitability, and efficiency, manufacturers must effectively handle unplanned machine downtime. Failure to do so can lead to production bottlenecks, wasted resources, and increased manufacturing costs.
In this guide, we explore the causes, costs, prevention strategies, and benefits of managing unplanned machine downtime effectively.
Machine downtime refers to periods when a machine is unavailable for production. There are two types of machine downtime: planned (productive) downtime, and unplanned (unproductive) downtime.
Unplanned machine downtime can create inefficiencies and reduce production efficiency. It can occur for multiple reasons, but common examples include machine malfunctions, operator availability and maintenance. We'll look more at the root causes further down in this article.
Knowing the top causes of unplanned machine downtime is essential for manufacturers looking to increase production capacity. Historically, getting accurate data behind the root causes of downtime relied on manual data capture. However, modern downtime tracking software offers an easy way to monitor when and why machines are unavailable for production.
Using tools such as machine monitoring enables managers to make informed to target the top causes and focus their efforts on removing them.
Unplanned machine downtime, if not monitored correctly can cause a number of operational and commercial issues for manufacturers. Understanding the causes of machine downtime, by machine, cell, production line or factory, and being able to do something about it, can drastically improve a manufacturer's operational efficiency, overall productivity, production capacity and profitability.
Unplanned machine downtime can also cause staff frustrations, leading to lower morale, and potentially leading to a high staff turnover.
Ultimately, when machines are down, production halts, leading to delayed orders, lost revenue, and potential damage to customer relationships. Additionally, machine downtime can lead to increased labour costs, as employees may need to work overtime to make up for lost production time.
As we have mentioned, unplanned machine downtime left unchecked can cause significant issues for manufacturers. Let’s take a look at direct, indirect and hidden costs associated with production downtime.
According to Forbes, the average manufacturer sees around 800 hours of downtime per year - more than 15 hours a week. This isn't cheap: for example, the same article states that the average automotive manufacturer loses $22,000 per minute when the production line stops, while unplanned downtime costs industrial manufacturers up to $50 billion a year.
Moreover, the actual cost of unplanned downtime goes beyond the immediate financial loss. Missing customer orders or having to turn down new customer orders due to production constraints can lead to reputational damage.
Beyond the immediate costs, there are also hidden costs associated with machine downtime. For example, unplanned downtime may lead to materials going to waste, which will take time and money to replace.
To mitigate the impact of unplanned and unproductive machine downtime can have on production capacity, manufacturers need to track it accurately.
Machine downtime monitoring technologies such as downtime tracking software are enabling manufacturers of all sizes to know the root causes of their equipment downtime, so they can prioritise where to focus their efforts to reduce or remove the top causes of machine downtime.
Machine downtime doesn't just affect a company's bottom line; it can also have a significant impact on employee morale. When machines are down, employees may be unable to complete their tasks, leading to frustration and decreased job satisfaction. Over time, this can lead to higher employee turnover rates, which can further increase costs for the company.
Proper training can play a crucial role in reducing machine downtime. When employees are well-trained in how to operate and maintain the machines they work with, they can identify potential issues before they lead to significant downtime. Additionally, training can help employees respond more effectively when downtime does occur, helping to get machines back up and running more quickly.
Utilising continuous improvement and Kaizen methodologies can encourage behaviours that reduce machine downtime. Continuous improvement is a fundamental principle of business that seeks to enhance and optimise company performance and output.
The model involves identifying a business area that needs improvement (in this case, machine downtime), implementing changes on a small scale, and monitoring results. Once complete, manufacturers can scale successful iterations across the business to reduce downtime across the factory floor.
Kaizen embodies the philosophy of continuous improvement through small, incremental changes. It emphasises the importance of ongoing learning, adaptation, and optimisation, and can be implemented across the workforce to encourage higher levels of productivity. Implementing Kaizen requires employee involvement, and encouraging their active participation, feedback, and suggestions will help minimise unplanned machine downtime.
Preventing and managing machine downtime involves a combination of proactive maintenance, effective training, and utilising manufacturing technology such as downtime monitoring software.
By identifying potential issues before they lead to downtime, manufacturers can keep their machines running smoothly and efficiently. Some key tips for manufacturers to prevent downtime include:
Regular maintenance and inspections: A proactive approach to maintenance and inspections will help you identify and prevent potential issues.
Implement relevant training: Ensure operators are trained to maintain machines to prevent issues and limit their impact if they do arise.
Keep an inventory of spare parts: Ensure you have the necessary spare parts ready to limit downtime if a machine requires maintenance.
Upgrade and modernise: Regularly assess the quality and performance of your machines and upgrade when necessary.
Real-time monitoring: Use downtime monitoring software like FourJaw to detect potential issues early and use real-time data to make informed decisions to minimise the impact on production.
Manufacturers can collect downtime data in several ways, including manual tracking, using machine sensors, or software solutions like FourJaw's downtime tracking software. These tools can provide real-time data on machine performance, helping manufacturers identify and address issues before they lead to significant downtime.
By reducing and, where possible, removing unplanned downtime altogether, manufacturers can benefit from increased production capacity, which means more products can be made with the same resources.
Learn more about increasing manufacturing production capacity.
Downtime tracking software helps identify incidents caused by human error. This can help managers improve labour utilisation by training staff and giving them the right tools for the job.
Accurate, real-time machine data collection eliminates the bias inherent in manual data collection. This leads to more informed and confident decision-making, allowing managers to devote time to issues that will deliver the best results most cost-effectively.
Downtime tracking software can help improve availability and performance. Ultimately, this will limit downtime and improve OEE, thereby improving efficiency and reducing maintenance costs.
View our blog on how manufacturers can benefit from OEE and implement OEE machine monitoring.
Downtime tracking software can help identify the causes of quality loss at the machine level. This information will help manufacturers identify potential quality issues and make any necessary adjustments.
The data collected and analysed by downtime tracking software can be used to optimise, change, or adjust production processes, leading to reduced downtime and improved efficiency.
Learn more about continuous improvement and see how manufacturers can implement Kaizen.
FourJaw is a leading provider of manufacturing analytics software, and machine downtime monitoring is one of the key features of our platform. Our platform captures real-time productivity and energy usage data to enable manufacturers to become more efficient, sustainable and profitable.
Manufacturers trust our technology and use it as an operational tool to support their continuous improvement strategies and lean manufacturing methodologies.
For example, FourJaw's software can provide valuable insights to help manufacturers implement Single-Minute Exchange of Die (SMED), a lean manufacturing method used for quick and efficient production setup and changeover.
By minimising machine downtime and streamlining setup components, SMED can lower manufacturing costs, enable more frequent product changes, improve customer demand responsiveness, and reduce errors.
A contract manufacturer, struggling with significant machine downtime due to on-machine programming, turned to FourJaw for a solution. After implementing FourJaw Pro to monitor their CNC machines, they discovered that programming was causing 3.49% of all downtime, costing over £100,000 in machining time.
This insight led to the strategic decision to hire two experienced CAM engineers, effectively eliminating the inefficient process and saving the company thousands.
Read the full case study here.
As technology continues to advance, new solutions are being developed to help manufacturers manage and reduce machine downtime. From advanced predictive maintenance tools to machine learning algorithms that can identify patterns and predict failures, the future of machine downtime management is promising.
In conclusion, machine downtime can be a significant problem for manufacturers if gone unchecked and its effects can harm the operational, reputational and financial aspects of a business.
However, with the right tools, training and processes, manufacturers can reduce machine downtime, improve efficiency, and ultimately, boost their bottom line.