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Capabilities accelerate


Supercomputers and the software running on them are revolutionising ways to do business. Richard Barrett asks several experts in the ERP and AI sectors to identify present digital trends and the future capabilities emerging

To get to grips with current trends in – and the new functionalities of – enterprise resource planning (ERP) systems and software, a brief reminder of their role is helpful.

If a business is likened to a complex organism like a human being, in some ways an ERP system is like the skeleton. It provides a structure, or framework, within which all the major parts of an organisation function and digitally connect. The system and the software modules that plug into it collect and organize business data, and then process and analyse it as an aid to making decisions and taking actions.

To extend the analogy, human eyes, ears, nose and nerve endings are akin to the sensors and cameras increasingly distributed around industrial plants and their machinery. The information that they collect is transmitted to the brain (computer) via the nervous system (internet, wireless, infrared or microwave transmission), where conscious or subconscious thought (conventional and artificial-intelligence (AI) software) processes and uses the data received to enable decisions about appropriate actions or reactions. Those are achieved via impulses sent, for example, to muscles providing motion (motors, gears and drives).

A prominent international ERP system and business software provider, SAP provides several different sizes of ‘skeleton’ scaled to the size of a business. For example, SAP S/4HANA for large enterprises is the company’s current collection of ERP software, which runs on top of its HANA in-memory database. SAP’s ERP system is complemented by the company’s own SAP Cloud Platform, which enables the agile building of custom applications or extensions.

Other cloud platforms include Amazon AWS, Microsoft Azure or Google Cloud. Some users still prefer to run their ERP system on their own data centres at their premises, while others will use a mixture of both, connected through firewalls to control the data flow between them.

To work within that framework, SAP provides, enables and interconnects hundreds of applications serving business processes across an enterprise. They include data management, procurement and networks, analytics, customer engagement and commerce, the internet of things, digital supply chain, human resources and finance.

Industry-specific value
While many business processes are generic, their combination and practical value is often industry-specific. So what are the most active users of SAP’s software in the mining, metals and steel sectors achieving with it today?

Stefan Koch, SAP’s global lead for metals, identifies several integrated steelmakers in eastern Europe as good examples. The Ukraine’s Metinvest and major Russian steel producers Severstal, OMK and NLMK are amongst them. Having started introducing SAP ERP systems to their businesses in the early-2000s, they have expanded them piece-by-piece with the latest new modules required, says Koch. “They have rolled out a lot based on their business context and strategies at the top level,” he explains.

For example, Metinvest, a vertically integrated group of more than 30 international companies with headquarters in Ukraine, has operations from mining steelmaking raw materials through to the production of finished steel products. The company’s IT strategy is based around effectively connecting its staff – numbering over 100,000 people – and locations and on reinforcing its links with customers.

Supply chain planning to optimize the use of the production capacities at the group’s 12 production entities is one established area for Metinvest’s IT program. It has optimized logistics serving over 700 demand locations with the aid of SAP APO, achieving substantial operational cost savings in the process.

Metinvest has embraced SAP’s platform and software in particular to support many key areas of business focus. Those include: growth in competitiveness, which requires improved client awareness, ready access to information and opportunities to benchmark performance; supply chain globalization, meaning that clients’ expectations for shorter lead times will grow; and changes in macroeconomic environment, such as more volatile markets and greater geopolitical risks.

The company has started to implement SAP integrated business planning software to support the whole cycle of planning, including long-term strategic planning and detailed production scheduling. Metinvest has also centralized raw material procurement and has started to implement SAP Ariba to maximize the efficiency and minimize the costs of its purchases.

In a business project led by Metinvest’s sales chief, the company has also started a strategic initiative to transform its sales division and maximize its level of service for customers in competitive markets for its steel products. Customer relationship management software is in the process of implementation to support that project. Human resources and talent management are another area being supported by IT systems.

Best practices are being shared company-wide via a cloud platform connecting all of Metinvest’s international facilities. Metinvest migrated to the SAP HANA Enterprise Cloud, which it started using in mid-2017, and it expects improved response times, system stability and data security, in addition to overall on-going software license cost savings, to result.

SAP Multiresource Scheduling and Work Manager modules do what they ‘say on the tin’. Both of them are being used by Metinvest, which also plans to use SAP Predictive Analytics to optimize the maintenance and servicing of the company’s wide range of equipment of various ages. Integration with industrial plant automation systems data is a key part of achieving this. This is also a stepping stone towards smart plants.

Whether users of SAP’s ERP systems prefer their software provided as a service through the cloud or installed locally, users can also install their own applications or those purchased from other vendors within the framework it provides.

“It’s all about having a flexible toolkit to enhance the business process,” Koch summarises.

What’s new?
IT now is about how to more flexibly adjust processes beyond existing conventional core processes. Cash and payment management processes are becoming increasingly automated, for example.

Existing users of SAP systems provided on a cloud-based software-as-a-service basis receive quarterly releases of software updates. Those running software on their own on-site data centers receive updates annually.

SAP provides ‘roadmaps’ to indicate the direction of travel. For example, at present SAP is looking to more tightly integrate transport and warehouse management modules with the S/4/HANA ERP system. The company is also enhancing its integrated business planning solution, using different algorithms to introduce new features.

SAP Leonardo is the company’s “Digital Innovation System”. It provides a platform within which companies can introduce the merits of new digital technologies for their business. It also provides a bridge to connect and/or embed the new technologies that suit them – in areas such as the internet-of-things, machine learning, advanced analytics, big data, prototype designs or blockchain – to their existing ERP systems.

Predictive maintenance is a tangible facility already emerging from machine learning, which is also feeding into the goal of predictive quality for products emerging from a mill. As of now, the use of artificial intelligence is to build on detailed existing production process knowledge, data and algorithms that are already held by plantmakers, and sometimes the companies using their equipment, to extend that knowledge via the ever-growing use of sensors measuring the process parameters used as the basis of analysis and simulation.

Koch says that specialized players can stream such data to the HANA platform and apply machine learning to process the numbers and look for recurring patterns and correlations. “Machine learning based on data from machinery, product measurement, as well as customer feedback on product quality, all feeds into Industry 4.0 and improving the production process,” Koch summarises. While some of these elements are not part of the ERP system itself at present, “SAP tries to bring the business to the operations world,” he explains.

Asset intelligence network
SAP recently started its asset intelligence network, which Koch describes as being like “Facebook for machines”. It has been launched in recognition of the fact that large manufacturers use – and need to maintain – machines and equipment from many different suppliers, while plantmakers and machine-builders supply many different clients globally. Just keeping track of the health, maintenance schedules and spare-part inventories for large ranges of equipment can be a challenge, so the asset network is designed to provide “a common platform for everybody,” notes Koch, who adds that such harmonization could save large amounts of time and money.

For example, options for service and safety checks for a particular machine can come via the platform. Large international chemical manufacturer BASF is one SAP user evaluating the network’s potential, together with how it could be used to change the existing processes to business advantage.

The cloud-based collaborative digital network can provide an industrial manufacturing company with a connection to multiple original equipment manufacturers and service providers and their respective asset data. The project’s goal is to establish a fully integrated and centrally managed repository of asset information, helping to ensure consistent and ready access to up-to-date data.

Improving worker safety
For companies getting to grips with the possibilities of machine learning technology, SAP has also devised a ‘co-pilot’ to harness others’ collective generic experience to provide guidance as to how it is designed and where it could be deployed – potentially positively disrupting some processes.

A very practical use of devices similar to the new fitness-monitoring bands worn on the wrist is the tracking of workers’ location and well-being around a plant. This technology would ensure that they are wearing the right safety equipment, and have had appropriate training, to enter hazardous areas, and can generate warnings if they are at risk of injury from, for example, mobile equipment such as overhead cranes or plant vehicles.

Koch explains that it can be a challenge to bring together all of the elements of safety technology needed to provide such a wide-ranging contextual system together, but SAP Leonardo is being used to launch such a system, including cameras combined with pattern and facial recognition to ensure that workers have the right safety gear for a given job.

NLMK-SAP Innovations Lab, together with Russia’s National Centre of the Internet of Things, has developed a pilot three-dimensional positioning system for factory-floor workers at its hot-dip galvanizing line No.1 at NLMK’s major integrated steelworks site in Lipetsk. It uses the SAP cloud platform, RTLS-UWB positioning system, 3D imaging technology and LoRaWan wireless communication technology.

Crowe Horwath’s solutions
Crowe Horwath is continuing to build on the range of features and functionalities of the Crowe Metals Accelerator (CMA), which it describes as “an industry-specific, scalable, and robust ERP solution specifically designed to meet the unique needs of the metals industry.”

Serving metal producers, processors and service centers, its scope already includes product information management, sales and customer service, procurement and sourcing, pricing, costing, production control, inventory management, warehouse and transportation, quality, and planning and scheduling.

Andrew Callaghan, a principal in Crowe's Performance Services group, helps metals companies to streamline operations, reduce costs and achieve more profitable growth through implementing CMA with Dynamics 365 – Microsoft’s flagship enterprise software. He explains that, from a metals standpoint, a significant advantage of combining CMA with Dynamics 365 is embedded Business Intelligence (BI) and machine learning capabilities, meaning that those are closely integrated with ERP packages.

Identifying KPIs
Crowe Horwath works with the metals sector to identify a collection of key performance indicators (KPIs) that act as a good starting point. The menu of options created can then be adjusted or refined to suit a particular company’s needs. Callaghan notes that different companies
use different formulas to arrive at the same KPI. They take into account factors such as inventory turns, margins, velocity and profitability alongside their balance sheets.

What influence does company size have? “Smaller companies want to act like bigger ones as best they can,” says Callaghan, “but they don’t have the resources to commit.” That is another reason why it is an advantage to have what they will need “baked into the product,” he adds. Not every company will want or need to use all of the functions of CMA and it is not just about ERP.

CMA’s ability to scale flexibly to a company’s needs through Microsoft’s cloud-based Azure platform – through which a business can lease data storage and processing/computing capabilities, rapidly set up and ‘dismantled’ according to demand without the need for capital expenditure on its own physical hardware – is attracting people to the product, says Callaghan.

Crowe is investing in artificial intelligence and machine learning and has its own data science team deploying across a range of sectors, including metals. Demand forecasting and predictive maintenance are two areas receiving particular attention, which Callaghan explains can be enabled on the cloud via Microsoft’s Azure platform.

“Everything is in the cloud now,” says Callaghan. “Patterns and correlations are used to feed into forecasting models,” he explains. In addition to monitoring the health of a plant through the internet of things in order to better predict, and thus avoid, machine failure, contextual product recommendations similar to those already experienced on sales platforms like Amazon’s – ‘if you’re buying this, you may also want this or these too’ – are entering the business-to-business world, based on past patterns in buying behavior. That is a valuable feature for service centers, for example.

Callaghan says that artificial intelligence is used to decide to pursue something and then act on it. Machine learning algorithms are used to effect the action decided. In his view, Microsoft has both the tools and the cloud-based computing power needed to enable companies to access software providing both.

By: Richard Barrett

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