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From Daimler to a Small Italian Supplier, 3 Enlightened Digital Moves

Feb. 6, 2020
Automakers’ approaches to adopting new technologies, and updating systems they already have.

Looking over IndustryWeek’s June piece about AI in auto manufacturing, it struck me how big of a challenge traditional manufacturers have ahead of them. Take carmakers, for instance – they are struggling with tariffs, escalating materials costs and changing customer expectations. Competition has expanded to include tech companies such as Uber, Google, Sony and Apple, who are rolling out conventional cars, autonomous vehicles, drones and other disruptive innovations.

To stay ahead in this competitive market, manufacturers have to transform their operations, as well as how they interact with customers. They have to adopt new technologies and update the systems they already have. They have to drive improvements from front office to back, from administration to the plant floor. They have no choice.

Some transformation initiatives are ahead of others. The innovators are taking advantage of next-generation technology platforms that connect their businesses, revolutionize processes with intelligent automation and enable them to make better decisions faster with embedded analytics. Homing in on carmakers as an example for the wider manufacturing space, here are a few moves they are making:  

Integrating Sensors into Predictive Maintenance

Predictive maintenance in factories focuses on identifying patterns in data that will flag changes in the condition of plant equipment. Car manufacturers have long deployed technologies that attempt to sense wear and tear so they can accurately determine when a plant, machine, component or part is likely to fail. Until recently, their efforts generated more misses than hits.

Today, a few key technology levers – machine learning, cloud computing and the Internet of Things – are accelerating the industrial revolution by enabling more effective systems for predictive maintenance. These systems collect data from machines and employees, and once data is collected and normalized, companies can apply predictive analytics to assess components’ prospects for continued operation.

Indus Motor Company, Pakistan’s second largest car maker, is equipping its manufacturing plants with sensors that will detect the impacts conditions such as humidity and temperature have on plant systems. While the project is in its early stages, officials expect the sensors will limit plant downtime and stave off early degradation of machine parts.

Indus also has created a defect tracking app to spot flaws in product parts. Sensors along the production line send data to the company’s upgraded ERP system, where it gets analyzed in real time. Having data processed quickly enables team members to take corrective action before problems multiply. Indus has already reduced the number of defects per unit by 20%. Officials say they envision a day when the smart factory automatically orders a replacement part immediately, once a reading reaches a certain threshold, perhaps even before a team member notices the exposed flaw.

Creating Next-Gen Global Supply Networks

Supply chains need to be driven by data to take full advantage of business opportunities – and business conditions – across the world. Data needs to be collected from as many sources as possible, and processed quickly, to create wide ranging insight that can impact the supply chain’s operations. These insights can help companies optimize their supply chains based on informed analysis rather than guesswork. They also can help monitor performance of certain aspects so they can be maintained and improved.

Daimler, one of the world’s biggest makers of premium industrial and commercial vehicles, recently conducted an extensive IT upgrade to get its global supply chain “future ready.” Its old supply chain management system, based on a legacy ERP system, struggled with fragmented data collection and sharing processes. Daimler addressed the problem by moving core processes to the Azure cloud and integrating a new purchasing and contract management capability onto a new IT infrastructure. This move to digital sped up order flows and gave the company a centralized system for planning and controlling of global material flow.

Doubling Down on International Traceability of Products

Product recalls cost the auto sector more than $20 billion a year. Flawed parts have long been an issue in the industry, and recent lawsuits charging manufacturers with moving too slowly to remedy situations are compounding the problem.

The importance of having full manufacturing traceability was not lost on OMR Group, a small Italian auto maker, who set out to embrace an aggressive IT transformation. OMR scrapped paper-based and manual processes that had served the family-owned business for more than 40 years and instituted a new IT backbone based on S/4 HANA.

Plugging in a manufacturing intelligence and integration system, operators now have direct access to a range of production and parts data right on the production floor. Previously, data was entered into the system days later, and error rates from transcriptions were high. Now, operators have direct access to data on touch screen monitors. This new ability to connect production systems right through to delivered products has helped OMR executives make more timely, targeted decisions and do a better job tracing products. 

The Future of Manufacturing

Car makers – and manufacturers overall – will continue to face challenges as consumption patterns and business conditions change. Manufacturers have made significant steps automating functions and driving intelligence through plant systems, and further evolution – in Industry 4.0 – will be needed as technology continues to disrupt processes. Deployment of newer, smarter technologies in the future will help them stay a step ahead of their competition. 

Georg Kube is global vice president Industrial Machinery & Components and Automotive at SAP.

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