Debunking 13 Conventional Myths About Smart Manufacturing

The biggest bottleneck in the implementation of Industry 4.0 for most manufacturers is the perceived low ROI. However, the rapid advancements in the technology landscape have created many attractive business cases. For instance, across Industry 4.0 technologies, economies of scale are equipping service providers to reduce prices. As the technologies themselves are innovated, their production processes further reduce operating costs and increase the potential ROIA (Return on Invested Assets). Manufacturers need to evaluate the basis of the investment not only on the cost of purchasing the technology but also on supporting accessories and infrastructure, training employees, consulting, and building new processes, which makes a far more compelling reason for adoption.

With devices becoming more capable and adaptable, the need for supporting infrastructure, systems, and support hardware has also reduced significantly. All these factors combined potentially reduce the overall investment for manufacturers and improve the ROI. Moreover, there are indirect cost benefits attached with Industry 4.0, such as improvements in factory throughput or overall equipment effectiveness directly impacting plants’ capacities and ability to serve customers and improving customer experience. High-precision Industry 4.0 technologies better product quality and lower the amount of scrap, rework, and repair cost.

Moving beyond traditional automation, the smart factory is essentially a fully connected and flexible system, which uses a constant stream of data from connected operations and production systems to learn and adapt to new demands. Tech tools such as advanced planning and scheduling using real-time production and inventory data or augmented reality for maintenance have already found wide acceptance in the smart manufacturing ecosystem. An all-encompassing smart factory moves beyond the shop floor and captures the enterprise and broader ecosystem.

A smart factory integrates data from system-wide physical, operational, and human assets, which helps drive manufacturing, maintenance, inventory tracking, digitization of operations through the digital twin, and other types of activities across the entire manufacturing network. Such transformation results in efficient and agile systems, less production downtime, and a greater ability to predict and adjust to changes in the facility, gaining a competitive advantage.

Adopting Industry 4.0 and building a smart factory is a continuous journey, which allows companies to realize value at a much quicker rate. This requires building a step-by-step foundation through the right data infrastructure and data acquisition processes. These fundamental aspects deliver greater insights into scaling Industrial IoT initiatives at a much faster rate. With people, processes, and data changes, machine learning technologies keep functioning in a continuous loop.

Such a methodical approach allows manufacturers to create and transform to a smart factory more quickly and with less hassle. To substantiate this fact, IDC has predicted that 20% of G2000 manufacturers will have transitioned to intelligent manufacturing by 2021, reducing execution times by up to 25%. The benefits of the smart factory can be achieved in the desired timeframe if companies think big, start small with manageable components and scale quickly to grow the operations.

As big data is making its way into turning today’s manufacturing into the smart manufacturing of tomorrow, data scientists are increasingly finding their place in this setup and are regarded as the new factory workers. Globally renowned companies such as GM and Ford have been integrating data in huge quantities from external and internal sources, from processors and sensors, to enhance their production capabilities. Even smaller businesses have also joined the race and are hugely benefiting from the use of big data because big data is cheaper to use and cheaper to store.

From AI-powered applications with predictive and prescriptive analytics to easy-to-use data visualization software, the analysis and optimization of production processes are no longer solely the role of Data Scientists. Plant Managers can also have live production data at their fingertips to make real-time decisions based on actionable insights. Process Engineers can analyze productivity based on historians and edge data on the shop floor or at corporate. This shift has created a new breed of analysts – the Citizen Data Scientist.

The real objectivity of Smart Factory is realized in integrating ‘dumb’ machines with ‘smart’ machines. The process starts with enabling data collection from those legacy machines. Manufacturers are gradually retrofitting existing equipment with smart sensors that collect comprehensive data in real-time. This data can then be passed to execution, production planning, and ERP solutions to provide full visibility into performance. This implies that manufacturing companies don’t need to replace their old machines with advanced ones. A perfect combination of the two is what makes a factory SMART.

One biggest misconception surrounding Industry 4.0 is that only large corporations can implement Industry 4.0 as it requires huge investments. However, this isn’t always the case. Yes, large companies come with the benefit of greater resources, and they are the early adopters. Small and medium-sized enterprises (SMEs) can also explore the immense possibilities of Industry 4.0 with limited resources.

First & foremost, companies need to realize that implementing a digital strategy doesn’t mean replacing existing systems with complex and expensive infrastructure. This ability to use existing equipment to communicate with new technologies eliminates the need to throw out legacy or older equipment. As explained earlier, new hardware systems can be retrofitted to older equipment to reduce expenditure. Sensors and other software platforms are also often very scalable and customizable options. Such solutions are cost-effective ways to collect process data and ensure that all their systems communicate effectively.

To start the transformation journey, companies need to develop a clear, enterprise-wide strategy in line with long-term business objectives and a roadmap for implementation. Digitalization among SMEs is critical to optimizing the supply chain for organizations of all sizes.

Industry 4.0, if implemented in its entirety, has the potential to catapult manufacturing paradigms. Tools such as AI, advanced analytics, automation, machine-to-machine communication, and the industrial internet of things (IIoT) individually have the power to drive big improvements in the manufacturing value chain. Industry 4.0 unveils a new era in manufacturing with universal connectivity, deep information analysis, and high levels of automation at its core when combined, which can alter how companies will be organized and lead in times to come. Industry 4.0 revolution creates a highly efficient and autonomous technological ecosystem that significantly reduces production costs and management time.