When it comes to the general public’s perception of digital disruption, a manufacturer might not seem to have much in common with some of the more high-profile examples of where this type of innovation is happening. After all, Uber transformed the travel industry without owning a single vehicle, and Airbnb upended lodging without owning a single hotel. A closer look, however, reveals that the same factors disrupting these service-based industries — namely, increased demand for customization and immediacy — are also having a profound effect on the manufacturing industry. Customers want a product or service that reflects their specific tastes, and they want greater control over how they purchase and interact with the products they consume.

For manufacturers, meeting these conditions by moving to a digital template requires transitioning from mass production to mass customization and implementing efficiencies across the ecosystem of the product life cycle, including suppliers, research and development (R&D), partners, and logistics operations. It means incorporating innovation into products throughout the manufacturing process, with the flexibility to produce new and different products without disrupting the production line. And it means an abbreviated fulfillment response time despite added complexity from customized production.

In a successful transformation to a digital enterprise, manufacturing is more closely intertwined with business strategy than ever before. From the placement of a customer order to the manufacture of a finished product, that strategy requires the ability to pivot instantly to variable demand and market conditions. SAP meets this need with a data-driven approach to responsive manufacturing that integrates information about every asset in the production line across the entire manufacturing process, from supplier to customer.

What Is Responsive Manufacturing?

Responsive manufacturing for a digital enterprise — for example, providing a customized product tomorrow based on individual sentiment data that was analyzed today — requires leveraging the Internet of Things (IoT), turning big data into actionable intelligence, and tying it all back to an enterprise system. It is the concept of integrating operational data with enterprise data — tying what is happening on the shop floor to customer data, supplier data, inventory data, material data, and cost data, and using it to transform the way business is conducted and increase your market influence. 

Collecting data, however, means little without the ability to understand what that data means for the business, the manufacturing process, and customers themselves. After all, connected machines have been around for a long time. Understanding how machines interact with one another in a lot-size-of-one production line is the new challenge.

Consider the increased importance of keeping production running for a lot-size-of-one production line, and how analyzing data in real time helps to achieve this goal. If a symptom of equipment failure manifests in one machine, but the root cause originates with a different machine, the manufacturer with instant access to real-time signals, predictive failure and maintenance analysis,¹ and all relevant data will be in a much better position to ensure that all stakeholders — the business, customers, suppliers, and original equipment manufacturers (OEMs) — experience minimal disruption. And this concept extends beyond the manufacturing floor. A vehicle manufacturer, for example, with real-time insight into the performance of a vehicle on the road can use this information to make relevant, timely changes to vehicles in production,² or to alert OEMs or outsourced contract maintenance of a part failure.

These are not hypothetical situations. Examples abound of manufacturers with digitization in play today. For instance, one SAP customer, an industrial manufacturer, has a 100-millisecond response time requirement to collect all digital information from a single piece of equipment, analyze it, and tie it back to the product, the customer that it is serving, and the entire extended supply chain. Other manufacturers routinely connect with SAP’s business network solutions, such as the Ariba Network, for instant access to a global community of potential new trading partners.

In short, responsive manufacturing means supporting a digital relationship with customers — for example, by ensuring production uptime or scaling for an influx of new customers — by integrating insight into manufacturing processes.

Manufacturing with Asset Insight

The number of IoT-enabled, smart devices that will flood the market in the coming years means more opportunities for manufacturers to incorporate insight into production processes. In addition, expanded automation in manufacturing processes driven by Industry 4.0 will increase the pressure on manufacturers to collect data from devices on the manufacturing floor in real time.

For a fluid production line that may have hundreds of pieces of equipment from a dozen or so vendors, maintaining high operational efficiency becomes a significant challenge. This is the challenge that SAP Asset Intelligence Network was designed to solve. Built on SAP HANA Cloud Platform, SAP Asset Intelligence Network helps customers manage all aspects of production holistically. With end-to-end visibility into equipment effectiveness, insight into how that equipment relates in the context of global operations, and support for predictive failure and maintenance analysis, manufacturers can better manage every asset in production.

SAP Asset Intelligence Network serves as a central repository for all information pertaining to a piece of equipment. This includes how that equipment relates to other machines, customers, suppliers, and OEMs. It includes parts documentation, maintenance records, information about what to do in the event of equipment failure, and automated alerts directed to appropriate stakeholders.

Previously, unconnected equipment usually meant unconnected processes for minimizing equipment downtime. It could mean training in-house technicians to become experts on certain pieces of equipment, the idea being that in the event of equipment failure, there would be in-house resources to remedy the situation. Of course, what would often happen is that once the training was complete, the equipment wouldn’t fail for some time, at which point the technicians had forgotten most of what they learned. It could also mean reaching out to various parts suppliers and OEMs for assistance, or, in a worst-case scenario, it could mean shutting down the factory entirely. SAP Asset Intelligence Network enables a connected process, allowing manufacturers to instead rearrange a production schedule based on the available equipment to significantly mitigate disruption, and even avoid equipment failure altogether with predictive analysis.

Even today, with predictive maintenance gaining a foothold in a burgeoning IoT movement and companies using data from sensors on manufacturing equipment to take proactive maintenance measures based on when a machine might fail, many OEMs still offer outsourced maintenance contracts for monitoring their equipment. But a transition to mass customization often means equipment will come from a far greater number of vendors, and maintenance for a single piece of equipment is insufficient to ensure high operational efficiency in a connected manufacturing line. Producing high quality products to meet customer demand requires the far more granular view provided by SAP Asset Intelligence Network of how each machine relates to every other machine in production.

Bringing Digital Processes into Production

It isn’t difficult to see how previous methods for ensuring operational efficiency become far less efficient in an age of digital manufacturing, where connected products and assets are tied to business results in a collaborative network of suppliers, vendors, and partners. By consolidating all of the formerly disparate information related to equipment in one location, SAP Asset Intelligence Network simplifies the way manufacturers manage these growing networks. Instead of chasing down vendors or spot-training technicians, manufacturers know that an OEM will have instant access to all the relevant information it needs to address an equipment failure — or even the potential for failure — and can address the situation accordingly.

The customer palate for customized products and smart technology that retain value long after purchase is becoming more discriminating — if a manufacturer cannot produce products that meet these refined expectations, customers are not prepared to wait. Manufacturers that expect to serve a digitally savvy customer base must bring digital processes into production. Connecting and managing these processes and assets with a singular, real-time platform — SAP Asset Intelligence Network — ensures a high standard of operational efficiency that matches the expectations brought on by digital transformation.

For more on SAP products that help support digital manufacturing, visit go.sap.com/solution/lob/manufacturing.html.

^{1 For more on SAP’s solution for predictive maintenance — SAP Predictive Maintenance and Service — see Dr. Achim Kruger's article “Drive Business Insight with Shared Asset Intelligence”. [back]}

^{2 For more information on how real-time insight can affect product design, see Thomas Ohnemus's article “Support for Connected Products Begins with Design”. [back]}