Unplanned non-operational time in production - how much does it really cost?

Unplanned downtime is all unexpected stops that occur during production. Such a stay occurs without notice and can last for a long time, thus leading to a loss of income. These unplanned interruptions in the production process eat up hours on the workday and the team and inevitably lead to losses and more costs. 
Accidents occur for a variety of reasons, even in well-organized production, even if accidents are kept to a minimum, they do exist. The time required to rectify the fault is directly related to the availability of the necessary repair materials, as well as the availability of qualified personnel to respond in a timely manner. These unplanned shutdowns turn directly into a loss of revenue. Any moment when a machine does not work without it is planned is a loss of revenue.

Some of the main losses are:

  • Capacity Loss - Each product that a manufacturer produces represents some amount of potential profit. Assume, for example, that a plant can produce 100 units per minute, and each of these units represents a potential $ 1 profit. For this company, the cost of downtime based on lost production would be $ 100 per minute, $ 6,000 per hour, and so on.
  • The increased cost of production - In regular cases of non-operational time, production managers gradually begin to anticipate this time as part of the cost of production. The unit price of a manufactured item becomes higher.
  • Increased labor costs - When you reduce downtime, production levels rise while labor remains the same. This will reduce unit labor costs. Also, when there are fewer problems, employees can focus on their main task and increase their efficiency.

How important is the focus on factory staff?
The intangible costs of downtime are less obvious as they are less specific. Much of this cost is focused on the relationships of the workforce in a given environment and how people and machines interact. Here are some examples:

  • Response time - In the event of an accident, employees should focus on solving this problem as their top priority. Because downtime costs are so significant, it becomes more important to address these issues than to focus on routine work. For example, the TDC in the automotive industry is about $ 22,000 per minute
  • Stress - Staying can cause a lot of stress to both employees and the machines they work with. In addition to stress and employee defocus, if a machine has to produce at its maximum capacity for long periods of time, it is more likely to fail. People and machines perform better with less stress.
  • Innovation - Staying takes a lot of business time, depriving you of focusing on other important things such as innovation and creativity. It is much more important to make sure that the current system works before looking for opportunities to improve it in the future.

Calculation of the true cost of the stay
The real costs of downtime are determined by the impact of the outage on employees and productivity. By identifying the costs of employee stays as well as the costs of losing orders, manufacturers can calculate the specific cost of unplanned operating time.
There are many reasons why understanding the cost of a stay is important for optimizing day-to-day operations throughout production. Understanding the importance of living costs, manufacturers can make data-based decisions with confidence. Operational teams can avoid unnecessary costs and preventive action can be taken to avoid significant amounts of unplanned operational time.
One of the popular ways to calculate the price of a 1-day stay is according to the following formula - lost profit per day /with 8-hour shift/ + costs for employees /their hourly rate and percentage of non-working employees due to an accident/ = total losses for an only 1-day stay!

How to reduce unplanned operating time in production?
A GE survey of the oil and gas industry found that only 24% of the global operators involved described their maintenance strategy as "predictive" or an approach based on efficient and effective data collection and management and analysis. The most common strategies used by the participants in the study are the reactive approach and the planned approach.
The main characteristics of each of these approaches in terms of unplanned operating time can be summarized as follows:

  • Reactive strategies average 8.43% for unplanned stays per year.
  • The planned strategies are on average 7.96% for unplanned stays per year.
  • The forecasting strategies are on average 5.42% per year for unplanned stays.

Combined with the additional costs of repairs, labor, transportation, and equipment, reactive and planned approaches result in losses of $ 60 million per year. A predictive approach to data monitoring reduces these losses by nearly 40%. The strength of the forecast data and analyzes lead to a significantly reduced amount of non-operational time, which can be seen in the production plant.

How to choose a platform for monitoring the stay?
The perfect solution for reducing unplanned operational time must combine both real-time monitoring and forecast analysis. Real-time monitoring allows manufacturing companies to access real-time production data. It allows you to see where refraction can occur in the production line, why it happened when it happened and much more. Machine learning and predictive analytics allow predicting and preventing problems by alerting operators or engineers in a timely manner so that they can take immediate corrective action, which will ultimately cost a 15-minute downtime against 5 hours of unplanned operating time in the future.
Stay calculation solutions are useful in many manufacturing industries today. Fabrico helps a number of industries limit unplanned downtime through the use of machine learning and predictive analysis. The solution is easy to use and made to benefit both workers and operators, as well as management that can easily monitor all operations. We at Fabrico strive to provide an easy-to-use tool to prevent unplanned operating time, saving a huge amount of money from lost revenue due to an accident or missed machine maintenance. Contact us for more information or a demo.

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