FEATURE Industry 4.0
The challenge of measuring Industry 4.0 RoI
By Alexandra Rangel, National PowerXpert Application Engineer, Eaton, Barry Turner, Technical Business Development Manager, Red Lion Controls, Kevin Goohs, Director of IoT Implementation Strategy, Omega Engineering, and Matt Dentino, IIoT Channel Manager, Advantech
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ndustry 4.0 is a set of powerful technologies and techniques that have the potential to transform the way many manufacturing companies do business. Using robots, automatic guided vehicles, autonomous cells, Internet of Things sensors and AI-based analysis, Industry 4.0 can help companies overcome the major challenges they face by providing better use of labour and equipment. It also helps continuous improvement and cost control by uncovering hidden capacity and optimising processes. While it can bring great benefi ts,
there are also major challenges in adopting Industry 4.0, with one of the most intractable being to prove that the project will deliver the required return on investment (RoI). Companies are accustomed to calculating RoI of new production machinery such as a new press that can produce more products with a lower cycle time, or a more effi cient motor that will reduce energy costs, but with Industry 4.0, RoI is more intangible since improvements rely on better use of data rather than physical counts and measurements. Ultimately, Industry 4.0 relies on smart technology to capture data that can be turned into knowledge that informs actions – if data is not being measured accurately, the process can’t be improved. With no improvements, the technology is not delivering a return on investment.
Three key areas for improving RoI Achieving the right RoI for a project and proving that it was achieved requires focusing on several key areas: • Assess key performance indicators. Industry 4.0 can help achieve improvements in product quality, effi ciency, production availability and energy consumption. Companies need to identify their relevant KPIs in these areas
12 June 2023 | Automation
and then track them before, during and after project’s implementation. In this way, manufacturers can demonstrate proven RoI. There may also be qualitative benefi ts that, while they don’t aff ect profi ts, can result in more eff ective operations by, for example, making data available in a more timely manner. This could allow earlier intervention in a process to get it back into specifi cation, hence avoiding losses and keeping product quality high. • Find the pain points.
The best overall strategy for implementing Industry 4.0 is to target areas with the greatest potential for improvements that could raise profi t margins. By focusing on the biggest pain points, data can be used to inform actions that improve performance. Achieving a reasonable RoI is best done through small projects that can show a measurable improvement over periods of 90 to 120 days. • Make more effi cient use of employees. With labour issues and skill shortages aff ecting companies’ operations, making better use of what can be an expensive resource is paramount. Using Industry 4.0 techniques means making better, more eff ective use of the workforce by avoiding the need to take physical readings of data from measurement devices and record the results on paper. Faster, more accurate readings ensure better quality and fewer complaints, boosting quality and effi ciency across the plant, which helps to achieve a high overall RoI.
Rapid access to good data Achieving a measurable RoI often depends on rapid access to data that can show where the improvements can be made in a reasonable time scale. This data needs to be aggregated via a dashboard, to display the essential information and insights that managers need.
New smart technologies are making it easier to collect and collate data rapidly,
which in turn makes it easier to manage, monitor and justify RoI. Farnell partner Advantech off ers a number of data collection solutions, ranging from smart sensors to wise modules with built- in intelligence. It also off ers backend solutions that enable users to ‘drag and drop’ diff erent types of RoI calculations such as overall equipment eff ectiveness and energy usage.
The cost of not operating Production interruptions from failed equipment can cost many hundreds of thousands of pounds in a short period of time. A recent analysis looked at a 315kW motor with a 95.5% effi ciency used in a continuous process. At an energy cost of 11p/kWh and with the motor running for 8,400 hours per year, the cost of running it over a 20-year lifetime would be over £6m. This is extremely high when compared to the typical purchase price of the motor at £18,000. Yet, the cost of not running the motor is equally signifi cant. The analysis cited an example of a motor used in the oil and gas industry, where such a failure could lead to losses of £220,000 an hour. That means a single stoppage of ten hours over the motor’s 20-year lifespan would lead to losses of £2.2m.
Investments in Industry 4.0 technologies can be justifi ed by referring to these types of potential losses. They are commonly caused by lack of experience of predictive maintenance, which uses data and analysis to determine which machines are in danger of going offl ine long before they actually do so.
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