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Downtime accounting and analysis


How can you reduce downtime and increase equipment productivity?

In 2017, ServiceMax, Vanson Bourne, and Aberdeen Research conducted extensive research into the impact of downtime on company performance. Thus, 82% of 450 surveyed companies had problems with unplanned downtime and it cost them about $ 250 thousand per hour. With an average downtime of 4 hours, the total cost of some businesses reached $ 2 million.
This is only the financial side of the issue. There are others: 46% of respondents reported that downtime caused a loss of customer confidence, and 37% felt the impact of reduced productivity on critical assets.
These statistics look pessimistic, but Industry 4.0 technologies are able to cope with unplanned downtime and breakdowns. You can read about technologies that solve these problems in our blog, and today we will talk about how to collect data on the basis of which you can make management decisions.

Accounting and classification

The first step to minimize risks in the operation of the equipment should be the creation of an electronic database, which will systematize the accounting of equipment downtime. Based on the collected data, a set of actions can be developed to improve production efficiency.
To assess the negative impact on work, it is worth classifying all downtime according to three basic criteria:
– emergency;
– planned;
– unscheduled.

At the first stage, this will make it possible to highlight the problem area – the technical condition of the equipment, the lack of resources or personnel, mistakes in the organization of maintenance and repair.

The second step is to classify the causes of downtime:
– defect, refusal or malfunction of the technical part;
– software problems;
– operator error and organizational deficiencies;
– unfavorable production conditions;
– operational overload.

It should be remembered that accounting for downtime can be considered effective only when the formalized classification of emergency situations is supplemented with context. It is the expanded context that will form the basis for developing practical solutions in the field of Asset Performance Management.

Analytical work and practical solutions

Information for the electronic database for accounting downtime can be collected by all interested participants in the production process – operators, shop managers, employees of engineering and technological departments. To do this, they must be informed and understand the main purpose of such accounting:

– get the most accurate data on the time and cost of downtime;
– identify directions to optimize the equipment work schedule;
– prepare the basis for the creation of an updated maintenance plan.

When the electronic accounting database is replenished with a sufficient amount of operational data, the analytical department will be able to calculate the technical readiness factor (KTG) and the equipment utilization factor (KIO). It is these two values ​​that allow us to assess the real productivity of production and develop an effective strategy to increase OEE (Overall Equipment Effectiveness).

Asset Performance Management Tools

When it comes to optimization, the key step is to move to digital data collection tools. Manual methods of maintaining the accounting base are hopelessly outdated. Paper reports and even Excel spreadsheets are time consuming to process.
You not only distract staff from important matters, but also slow down analytical processes. After all, non-contextualized information gets into the downtime accounting database, which requires additional processing before importing into MES (Manufacturing Execution System) or ERP (Enterprise Resource Planning).

A more progressive step is the use of digital tools to collect production data.

Key benefits of this solution:
– round-the-clock monitoring and registration of the state of equipment in real time;
– no restrictions on data collection due to external adverse conditions;
– automatic compilation of operational data into analytical reports;
– the ability to integrate accounting tools into the global production management ecosystem.

The last point is especially important, because accounting for downtime is only a component of larger projects based on innovative technologies. This data will then be used in work with Machine Learning, Digital Twins, IIoT Platforms, Artificial Intelligence, etc.
To summarize, let us emphasize once again that data collection is the first step that will allow you to manage equipment downtime. And along with them – and the overall productivity of the enterprise. The economic effect of such management will very quickly become noticeable.

At SmartEAM, we develop end-to-end solutions for the digital transformation of manufacturing in accordance with Industry 4.0 principles. In particular, we create Asset Performance Management systems that help turn reactive methods of dealing with unplanned downtime into an effective strategy for increasing the profitability of business processes. Leave a request.

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