Companies across the world are gearing up to pursue Industry 4.0 in letter and spirit. Many are adapting to the use of AI and machine learning to predict possibilities. Manufacturing companies are envisioning enhancing their manufacturing process and delivery lead time with the help of data and analytics and AI-based systems. Ewelina Gregolinska, Rehana Khanam, Frédéric Lefort, and Prashanth Parthasarathy are authors of the article, “Capturing the true value of Industry 4.0” for mckinsey.com. They argue that “The digitally enabled factory of today looks very different from the leading factory of ten years ago. Advances in data and analytics, AI, and ML-and the array of technology vendors in the market-mean manufacturers can choose from hundreds of potential solutions and tech applications to improve their ways of working.” The article discusses the concepts of blockchain, cloud technology, and the Internet of Things will enhance data and computational power.
The human-machine interaction will become the new norm in the era when Industry 4.0 will be fully implemented. This interaction will run effectively because of virtual and augmented reality, robotics, and automation. Perhaps the human-machine interaction will also augment human cognitive skills for they will be exposed to new information and ideas. Big data, in this regard, will be of paramount significance when it comes to applying analytics and intelligence in Industry 4.0. Furthermore, renewable energy and additive manufacturing, such as 3d printing, will guide the domain of advanced production methods.
It is expected that the value potential will enhance the returns. The inventory holding cost will be reduced by 15 per cent to 20 per cent while labour productivity will be increased by 15 per cent to 30per cent. It is also expected that machine downtime reduction will be 30 to 50 per cent. Forecasting accuracy improvement will be 85per cent while there will be a one to 20 per cent cost-of-quality improvement.
The human-machine interaction will become the new norm in the era when Industry 4.0 will be fully implemented.
When discussing Industry 4.0, companies need to create a cohesive team that works with a single-minded approach to achieve organizational goals. Achieving a higher rate of human-machine interaction, robotic automation process, and utilizing big data for predictive analysis will require teams to plan, think and act with the goal in mind. However, companies will be facing challenges as they try to adapt to the concepts of Industry 4.0. Companies should not work in silos, as the article discusses. The authors write, “By pursuing digital transformations as a theoretical exercise, many companies unwittingly set up independent delivery teams that are decoupled from business leaders, site operations, manufacturing excellence, and central IT.”
Adapting to failure is another reason for companies falling short to achieve their goals. A company cannot use the same formula applied for one product/service or market or another product/service or market. A company must offer a customized product or service with a perceptive understanding of the socio-economic and cultural factors of the target market. Moreover, the company needs to analyze the current market trends and link them with historical data to predict the future. Numbers and data have become an asset for companies that allow them to extrapolate the future. It helps them to offer and market their products and services accordingly.
The writer is an independent researcher, author and columnist