How to approach Industry 4.0 in the Mill Products Industry?
When Industry 4.0 2011 was announced at the Hannover Fair, many companies in the mill products industries (metals, building materials, paper, packaging, textiles) were left wondering why this was news. Many of the topics, such as data acquisition, sensors in the plants, and automation were not new to Mill Products companies as many started these initiatives more than 20 years ago. Accordingly, they did not initially see much added value in the initiative.
This situation changed fundamentally starting in 2016 with the emergence of new information technologies such as big data, advanced analytics, machine learning (ML), and artificial intelligence (AI) and the rapidly decreasing costs for their use. This can be seen, among other things, in the sharp increase in the number of use cases for this digital technology to gain new insights using existing process data. The emergence of cloud solutions also plays an important role, as many POCs (Proof of Concept) would not have been possible due to the high up-front investments for necessary hardware and software. In addition, the increasing spread of powerful mobile devices has made it possible, on the one hand, to collect data in a previously impossible level of detail, for example by taking pictures of the damage or spare parts, and on the other hand, to distribute information and support decisions in almost real-time.
A big advantage is that many Mill Products companies have been collecting process data from PLC or SCADA software systems already for years. Furthermore, compared to more assembly-oriented industries, the use of MES systems in the industry is more standard than exception. Thus, a large part of the effort required for the collection of process data is usually not necessary and a huge amount of data is already available to use.
Mill Products Companies are in an excellent starting position for Industry 4.0
In fact, most Mill Products companies are in an excellent starting position for Industry 4.0. As discussed, the significant progress in information technology for storing, cleansing, and processing raw data combined with the availability of cloud-based solutions enables companies to gain new insights from existing data with manageable effort in the context of POC. Consequently, many companies have already launched pilots for Industry 4.0.
There is a lot of room for improvement, however. Despite many encouraging results of POCs, the business value achieved in operations often falls short of expectations, as many companies state that they have not yet seen enough tangible benefits from the use cases. To understand this discrepancy, it is worth taking a closer look at some of these POCs. Many initial test projects focus on simply testing new technology to see how it works. How to expand these tests into actual operational usage is initially given little attention. For example, companies test the use of predictive analytics or machine learning methods in the area of quality or maintenance to make predictions about the development of the quality of a product or the wear of a tool. After a successful POC where the team confirms that a process works, the question often arises as to how it can be integrated with existing business processes to automate and optimize them. This requires a different skillset especially as it relates to human resources topics such as changes in how people do their jobs. This next phase can often require working with multiple other departments involving other subject matter experts and needs a different set of plans and execution.
Another challenge is that many POCs tackle only one part of a bigger end to end process. For example, many projects in the area of predictive maintenance end with the creation of a maintenance order. But ending with the creation of a maintenance order is not enough to leverage the full potential of Industry 4.0. The real value comes from taking the next step in the process – identifying and planning the required spare parts and combining the maintenance measures with other planned actions to optimize the total downtime.
This example clearly shows that one isolated individual POC is often not sufficient to realize the full potential of Industry 4.0. This requires a comprehensive, holistic strategy that considers not only the technology but is also tightly interlock with the business processes.
This is exactly what SAP Industry 4.0 initiative, called SAP Industry 4.NOW, is aiming at. It is designed to support companies in implementing Industry 4.0 as a company-wide initiative.
Industry 4.0 supported by the Intelligent Suite
The intelligent suite plays a central role in implementing Industry 4.0. Many customers see it as the foundation for a digital transformation towards Industry 4.0, as examples from metals companies Metalloinvest and Tata Steel show.
One reason for this is that SAP software solutions, including SAP S/4HANA, are increasingly moving towards data-driven processes and connecting manufacturing with business processes for better and more informed decision-making. For example, a direct connection of level meters from silos or containers can automatically initiate a replenishment order. Examples from cement provider, intelligent hygiene maker Hagleitner Hygiene, and VIZUU, a subsidiary of the globally active fabricated metals producer SCHÄFER WERKE Group, show that besides the automation and optimization of business processes, completely new business models open up for mill product customers, as they develop from a company that focuses on the sale of products to service and value-added oriented company.
Quality management is also poised to gain significantly from the new possibilities that Industry 4.0 offers. For example, the result of the quality check on the level of quality characteristics can be used directly for a profit optimized allocation of customer orders as an example from Severstal shows.
These examples also show that many processes that were previously clearly assigned at the MES level can now run directly in the ERP system, expanding ERP closer down to the shop floor and thereby blurring the traditional boundaries between MES (Level 3) and ERP (Level 4). In this way, existing business processes are extended with Industry 4.0 capabilities. Real-time data, insights, and analysis from sensors enable companies to predict maintenance needs, quality issues, or problems with manufacturing processes in advance. Combined with customer preferences, these data-driven insights increase supply chain transparency, automate process steps, lower material costs, reduce risk, and significantly decrease asset downtime.
The factory of the future
A further criterion for the use and provision of applications on a large scale is the standardization of the data basis and the manufacturing landscape. Data for the same use-case, but coming from different systems, can usually only be compared to a limited extent or at high effort due to the different semantics of the data. A heterogeneous system landscape also stands in the way of the scalability of Industry 4.0 innovations. Therefore customers such as packaging giant Smurfit Kappa or metal tools provider Kennametal invest in this area to drive Industry 4.0.
This data can then be used as one starting point for numerous use cases in the areas of predictive quality, predictive maintenance, and data-driven process optimization, as customer examples from Steinbeis Paper GmbH and ALBIS PLASTIC show.
Worker Safety and People Empowerment
Another area that is facing fundamental changes using IOT technology is the area of worker safety. IoT devices using the LoRa (Low Power Wide Area Network) communication protocol not only allow to position workers in real-time but also enables companies to transmit health-related data like pulse or blood oxygen level to manually or automatically call assistance in case of an incident. The integration with applications like environment, health and safety (EH&S) enable numerous additional use cases such as alerts in case the worker entering a dangerous or unauthorized area, requesting support in an emergency, or ensuring the complete evacuation, as use-case from steel producers Tata Steel and NLMK shows.
All these examples show the tremendous value that can come from Industry 4.0 when operational data is collected along asset, machine, and product lifecycles and transformed into intelligent insights.
On the other side, this also shows why we believe that a focus on end-to-end processes is required to realize the full potential of Industry 4.0. Therefore, SAPs approach for Industry 4.0 is to embed intelligent technologies and process automation into business processes to enable new ways to solve business problems, generate new revenue streams and offer digital services that help you satisfy your customer.
SAPs Industry 4.0 initiatives allow customers:
- To build Intelligent Products that are designed to monitor and maximize performance over time, while meeting customers’ precise and unique configurations
- To build up Intelligent Factories, that use data and intelligence to run as autonomously as possible, while delivering both mass-produced and individualized products at scale.
- To leverage Intelligent Assets, linked to each and every process and dynamically maintained.
- And to Empower People that are equipped with the tools and information they need to do their best work.