Downtime is one of the biggest causes of production loss within manufacturing. Every minute that your machines are idle is costing you money. The biggest cost is unplanned downtime, where unforeseen breakdowns occur. This can have a big impact on the total number of units produced, and the consequent revenue created. But how much does this really equate to? Working out how much money is being wasted by having high downtime is a very worthwhile task. It can be that extra incentive to invest in measures to reduce downtime.
However, most companies find it very difficult to actually calculate their true cost of downtime. As such, this blog post will delve into how to calculate the true direct and indirect costs of machine downtime, and the things you can do to reduce downtime. If you missed it, check out our blogs on the causes and impacts, and the best ways to track downtime.
The Financial Impact of Downtime
Direct Costs
The direct costs associated with machine downtime are immediate and quantifiable. The most obvious direct cost is in lost production value. is the most apparent. Each idle minute means a direct loss of potential revenue, as you will create less units within that shift, and this time cannot be brought back elsewhere.
Materials prepared for production but left unused due to machine failure also represent a wasted investment. If you have materials mid way through production and something fails, this will often ruin the unit. Sometimes portions of the product can be saved, but often they need disposing of, which results in further wasted costs.
Finally, urgent repairs often incur high costs. Sometimes you may not have the specific part you need, which requires expedited shipping that can be very expensive. This is why it’s so important to have an accurate stock management system. All of these direct costs that we’ve mentioned can rapidly accumulate, impacting the short-term financial health of a manufacturing entity.
Indirect Costs
Beyond the direct expenses, downtime carries substantial indirect costs. If people receive their orders late, or worse not at all, then they will lose trust in the business. As such, they will not return, and this can lead to long-term revenue loss. Repeat customers are one of the best ways to increase revenue without having to increase marketing budget, so ensuring your customers receive a good experience is essential.
Another indirect cost can come from having to pay your staff overtime if they need to stay longer to fix the issue. They may also need to work overtime to meet the production target for that day. Both of these factors can inflate operational costs, further diminishing profit margins.
Perhaps most significantly, repeated downtime events can tarnish a brand's reputation, leading to lost future business and difficulty in attracting new customers. These indirect costs, though harder to quantify, can surpass direct expenses and inflict lasting damage on a company's financial standing.
Calculating Downtime Costs
According to a study by Aberdeen Research, unplanned downtime in manufacturing can cost up to a massive $260,000 per hour! And not surprisingly, downtime now costs 50% more than it did in 2019/20.
Calculating the cost of downtime for your individual business involves a multifaceted approach, considering both direct and indirect expenses. A basic formula involves the following:
Cost of Downtime= (Hourly Production Value x Hourly Labour Cost x Hourly Overheads Cost) x Duration of Downtime
However, real-world applications require inclusion of indirect costs such as loss of recurring revenue, and loss of future revenue from ruining relationships with customers. Adjustments also need to be made for industry-specific variables, such as the cost of lost opportunities in high-demand periods,
As such, the true cost of downtime formula would actually look something like this:
Cost of Downtime = ((Hourly Production Value x Hourly Labour Cost x Hourly Overheads Cost) x Duration of Downtime) + Loss of Recurring Revenue + Loss of Future Revenue
Of course, the last 2 factors are very hard to quantify, but this would give you the true cost of machine downtime.
Strategies to Mitigate Downtime
Preventive and Predictive Maintenance
One of the best ways to reduce downtime is the implementation of preventive maintenance schedules and predictive maintenance technologies. Regularly servicing equipment can prevent many common causes of failure, while predictive analytics can forecast potential breakdowns before they occur. This proactive approach minimises unplanned downtime and extends the life of machinery, contributing to overall operational efficiency.
Training and Continuous Improvement
A well-trained workforce is instrumental in minimising downtime. By ensuring operators are proficient in machine handling and aware of maintenance protocols, many potential issues can be avoided. Similarly, embracing continuous improvement methodologies like Kaizen encourages a culture of constant evaluation and refinement, leading to fewer errors and more efficient processes.
Technological Solutions
Leveraging modern technological solutions, such as downtime tracking software and Computerised Maintenance Management Systems (CMMS), can provide a structured approach to managing and reducing downtime. These tools offer insights into patterns of machine usage, maintenance schedules, and common points of failure, facilitating more informed decision-making and strategic planning.
Busroot, our manufacturing analytics platform, takes all the guesswork out of downtime. It uses IoT devices to collect real-time data on the status of all your machines, identifies the causes of downtime and provides you with a predictive maintenance schedule. It gives you visibility into every area of your production, and can help to significantly reduce unplanned downtime.
Machine downtime presents a significant challenge in manufacturing, with far-reaching financial and operational impacts. By understanding the true costs of downtime, manufacturers can highlight to stakeholders the need for investment into strategies to reduce downtime.
%20(1).jpg)
