Why Car & Electronic Manufacturing Has Looming Challenges and What Can Supply Chain Analytics Do About Them?

The focal point of this article is to increase the speed of decisions in OEM-based supply chains irrespective of their systems and locations. Tasks related to recycling and salvage will improve with full-scale, real-time visibility into inefficiencies and data-intensive prescriptions for action. Customer-end data is of significantly high importance in this case. Read more.

Supply chains in the manufacturing industry have a role to play in improving customer experience over the long run. Manufacturers of cars, electronic products, and parts assembly are involved in a complex set of processes every day. Despite that, the OEM must live up to warranties, make goodwill strategies, and ensure that repair services not only satisfy but drive growth. The fact is that it costs.

In order to be able to provide an adequate budget for processes, reclaiming value from recycled parts is a recommended ‘way out’ for the discrete manufacturing industry. Let’s take a look at the tides and how a simple IT transformation can give you the ideal setup for business automation.

What measures can be taken for operational efficiency in any department (including recycle engineering):

  • Shift from desktop to computer (and on-premise to cloud)
  • Database management streamlined and largely automated
  • Real-time management analytics and simulations
  • Workflow transparency for efficient monitoring

The cost of warranty service is well known to eat into profits. On the other hand, doing repairs and marketing also comes with justifying the budget through some form of a customer-satisfaction score. Add to that the recycling cost, which could drive profits if cheaper.

The processes involved, such as shipping, analysis of the material, reporting, engineering, and pricing are part of an extensive lifecycle in the discreet manufacturing sector. The effective approach in any OEM is enterprise mobility that draws data from ERP, CRM, and big data. Making sense of every move is the mantra, no doubt, in the information age.

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Worries about disruption

Automation in the manufacturing sector has been a long story. Robotics and automated BI analytics are seen everywhere to some degree. The idea that technology will replace jobs may be easy to hatch. However, a more decision-oriented workforce has been the order of the day.

However, automation saves so much cost and helps you discover hidden problems that need attention, reducing the staff size is not exactly the focus. It is about shifting them away from inefficiencies. The perspective most leaders shared by adopting operational efficiency as the model sure expected workforce-related problems early on, but find that automation has only made the worker’s job more interesting and less tedious.

The typical enterprise technology of the day

SAP upgrades have recently made it possible to share real-time reports of complex data within a global enterprise set up seamlessly. It means decisions can be as quick as the rest of the enterprise moves. That’s the basic reason why the S/4HANA upgrade has people talking about its features ideal for management.

Why are recycling processes in dire need of enterprise mobility and real-time intelligence?

The importance of efficiency in a complex industrial process is evident. Things have to move fast, inexpensively, and lean. A cloud-based mobile enterprise is capable of shrinking operations and budgets. It relies on a system that automates information processing and customer communication besides revealing significant advancement in data capture.

What you may need to change in a big way

Machine-to-machine (M2M) communication is a significant part of automating the complex workflows of a typical discrete manufacturing company such as a car maker. The movements of parts (production, sale, and aftermarket) are crucial. The outcome of each part is related to a number of parameters, based on performance, design planning, and life cycle history. From time to time, OEMs need to analyze strategies related to those parts, whether it’s for recycling or improving a finished product.

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Ultimately, the data generated, combined with analytics, will give managers maximum clarity on every product life cycle stage through simulation.

Technological advantages for discrete manufacturing operations:

  • Goods visibility and monitoring: Using M2M technology and interfaces that reveal the workflow status and team efficiency
  • Better collaboration and service: Using a shared platform for real-time communication and advanced notifications for suppliers (includes parts tracking)
  • Continuous improvement: Using the data acquired from workflows, service delivery, and parts handling, an OEM can improve services. The parts themselves are studied as a regular discipline, and the data can be used to recommend a way to better products in the near future.

The application-based requirements of a company depend on its functionality. However, the applications can be customized based on the functionality, which you may want to revise before transforming IT or upgrading to SAP S/4hana integration (for adapting to an existing environment, SAP works with partners that plug in the technology flexibly for different industries).

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