We are at the cusp of the fourth industrial revolution. Known as Industry 4.0, it is proving to be a turning point for the automotive industry. While most automotive facilities are in a phase of evolving seamless human–machine connectedness, the industry as a whole has readily embraced the concept of Industry 4.0.

Simultaneously, consumer preferences have been edging towards greater connectivity with their automobiles, further encouraging the industry to evolve. Yielding to these rising demands, vehicle manufacturers are working hard to achieve digital maturity across their broader enterprises, by offering their best tech features in even their smallest cars.

In the journey towards Industry 4.0, auto companies can use Manufacturing Execution System (MES) as a bridge between the enterprise system (for instance, SAP) and handle the product complexity at the shop floor to link the market demand to production schedules at assembly, aggregate and component levels.

To speed up production, automakers can evaluate investments towards the following modules:

Machine utilization module: Efficiency of machine utilization can be increased by capturing real time data and analytics on Overall Equipment Effectiveness (OEE) and engaging the workforce to improve the efficiencies.

Engine volume prediction based on analytics: By capturing data of machined components, finished engine inventory, engine demand from general assembly in terms of product mix (petrol, diesel, turbo charged, etc.), performing analytics to indicate setup change / batch size, engine assembly sequence, shift planning, etc. to ensure seamless engine supply to general assembly

Maintenance module for uptime improvement: Enhancing machine features to capture early real-time signals of potential failures and relevant peripheral data to do analytics for prediction of potential failure mode

Smart energy management: Real-time mapping of energy consumption along with manufacturing data for optimizing energy consumption with support of analytical tools

Predictive quality management: Using advanced analytics to perform real-time quality-related data mining and analytics along with continuous monitoring

It is also important to redefine the value chain. With a wide array of IT platforms to choose from, the entire value chain can be integrated through IT by enabling transparent communication, faster information sharing and speedy decision-making. MES can help significantly in improving the production system.

The Digital Factory Simulation software for new line installation helps in building a process model for commissioning the analysis of the system and process before its implementation. Also, Product Simulation using Product Lifecycle Management and digital factory can help in quicker product launches and their production.

Autonomous and Connected Vehicles show the perfect bridge between the digital and real world. The demand for connected cars is shifting from early adopters to mainstream customers as ‘connectedness’ becomes the basic ask. Connected car technologies offer advanced connectivity features using artificial intelligence, machine learning and the internet of things as part of their phased autonomous vehicle programme. A connected ecosystem should ideally integrate into the digital lives of customers. One can work with technology partners to bring the digital lives of our customers into the cars they drive.

Besides significant investments in research and development towards developing advanced and emerging technologies, it is the right set of talent that will allow auto players to differentiate themselves.

Rajendra Petkar is chief technology officer (CTO) at Tata Motors

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