Industry 4.0 is one of the most trending technology terms of the last decade. It refers to a complete digitalization of physical processes based on the introduction of Cyber-Physical Production Systems (CPPS) and Internet of Things (IoT) devices in industrial settings like manufacturing shopfloors, industrial plants, and oil refineries. In the manufacturing sector, many enterprises all around the globe have recently deployed IoT and CPPS systems in their shopfloors, as a means of implementing use cases like flexible production lines, predictive maintenance, digitally-enabled quality management and Zero Defects Manufacturing (ZDM). Nevertheless, the implementation of these use cases is never an easy way out. It usually requires significant investments in systems and technologies like data collection devices and digital manufacturing platforms, along with the ever-important investments in complementary assets (e.g., training) that help establishing a digital culture inside the manufacturing enterprise.
In this context manufacturing enterprises must consider both the benefits and the costs of their Industry 4.0 endeavours. At the end of the day, Industry 4.0 projects must have a positive reflection on enterprise bottom lines. This is particularly important for smaller manufacturers i.e., Small Medium Enterprises, which typically lack the equity capital needed for investing in disruptive technologies without tangible and immediate returns. For these reasons, the implementation of Industry 4.0 projects should be accompanied by some credible estimation of their financial gains. This is a key to taking advantage of the Industry 4.0 benefits, while avoiding the hype.
To ensure that the potential benefits of an Industry 4.0 investment outweigh the costs, enterprises can employ capital budgeting techniques, such as Return on Investment (ROI) calculation. In simple terms, ROI is an indicator of the ratio between the net revenues and the original investment on an Industry 4.0 project. It can be used to compare alternative investments in terms of their financial returns. These alternative investments may be different Industry 4.0 projects, but also investments in other technological areas. In principle, the higher the ROI of an investment, the better it is. In practice, ROI is calculated based on the following steps:
These calculations are reflected in the following ROI calculation formula:
Return on Investment (ROI)= (Total Benefits – Cost of the Investment) / (Cost of the Invesment) X 100
One of the main issues with this formula is that it does not consider the time value for money i.e., the fact that money loses value over time due to inflation. This can be a problem for investments that take several years to generate profit. Therefore, in several cases other indicators are also used for comparing the financial benefits of an investment, like the Net Present Value (NPV) and the Internal Rate of Return (IRR) of an investment. Specifically, NPV is a monetary value that indicates the total benefits of the investment taking into account the time value of money. Likewise, IRR indicates the “equivalent” interest rate that if applied to the capital investment would yield the same net returns. IRR considers the time value of money and hence it is much more powerful than ROI when considering investments that span multiple years. Nevertheless, indicators like IRR and NPV are used in ways similar to ROI: They are vehicles for quantifying and comparing alternative investment options.
The calculation of any of the above-listed indicators boils down to calculating the benefits and to estimating the costs of an investment. Working on the part of the costs is quite straightforward: The aim is to calculate all the costs that are associated with the development, deployment, and operation of the new Industry 4.0 system, including for example hardware costs (e.g., new sensors or CPS systems), software costs (e.g., licenses for BigData databases and analytics development), integration costs (e.g., cost for integration with the legacy ERP (Enterprise Resource Planning) system), as well as costs associated with additional assets like new production processes and workers training. Key to the successful calculation of the costs of the investment is to consider all cost factors i.e., to calculate the Total Cost of Ownership (TCO) of the investment. In this direction, potentially hidden costs (e.g., legal costs, energy costs, and reskilling costs) should be also identified and accounted for.
The part of the benefits is always more challenging. This is because benefits might have to be estimated based on some operational scenario, which entails some degree of uncertainty. In principle, the benefits are typically reflected in increased revenues, increased productivity, or even reduction of production costs. Their quantification relies in the estimation of manufacturing performance parameters such as parameters relating to production cost, production time and production quality. These parameters vary depending on the type of Industry 4.0 use case considered. For instance, in a supply chain management project, manufacturers will have to track parameters such as order fill-rate, inventory efficiency and forecast accuracy. As another example, in intelligent asset management and predictive maintenance use cases, there is a need to track parameters such as Overall Equipment Efficiency (OEE) and the Replacement Asset Value (RAV) for various assets.
During the ROI calculation process, manufacturing performance indicators must be translated to monetary benefits. This translation requires expert knowledge, access to corporate data, as well as exploitation of international best practices about how improvement in these parameters improves revenues as well. It is usually a challenging, yet not impossible process, that hinges on the availability of the right data. The outcome of the translation process is a set of credible estimates about the monetary benefits of the project.
Capital budgeting methodologies like ROI and IRR calculation are among the best tools manufacturers have, when it comes to quantifying and assessing the merits on Industry 4.0 projects. Nevertheless, they are also associated with several limitations, which must be factored in the decision making of the business management. Specifically:
Any credible ROI calculation must be grounded on actual data and evidence stemming directly from the manufacturing shopfloor. Hence, ROI calculations can greatly benefit from digital manufacturing platforms that provide instant and direct access to manufacturing performance indicators. The Upkip platform provides a rich set of manufacturing performance indicators based on the analysis of a wealth of digital data from the shopfloor. Specifically, it supports the calculation of parameters such as: (i) Overall Equipment Effectiveness (OEE) at various levels e.g., per factory and per customer order; (ii) On Time Delivery indicators, such as information per order component (items), per department, and per customer order; (iii) Machine performance indicators such as CNC data for specific processes like drilling, mulling, and cutting; (iv) Customer Order performance parameters, including for example information on cost deviations and on-time delivery; (v) Waste and Quality Related Parameters, including scrap and waste related information at various levers such as waste per operator, per order, per machine and per tool used; and (vi) Sustainability parameters, such as temperature, humidity, wind speed/direction and how these data impact production quality.
These indicators are suitable for many different Industry 4.0 use cases, including predictive maintenance, quality management, supply chain management and sustainable manufacturing. Based on these indicators, Upkip enables manufacturing enterprises to derive monetary estimates about the benefits of Industry 4.0 installations, through benchmarking the state of the factory and of the production lines, before and after the Industry 4.0 system deployment. These KPI calculation functionalities come on top of many other Industry 4.0 functionalities and use cases that Upkip supports.
Furthermore, Upkip experts offer a rich set of professional services for manufacturers, including ROI calculation services. These services leverage the KPIs of the Upkip platform, while at the same time exploiting our experts’ knowledge on the ROI calculation process. Moreover, Upkip experts have developed a database of ROI calculation cases studies for different Industry 4.0 projects, which they consult when calculating capital budget indicators in-line with international best practices.