According to Modor Intelligence, the global smart factory market is projected to grow from just under $212 billion in 2017 to $358 billion by 2023 — a CAGR of 9.17%. Such momentum is justified by significant operational benefits that a smart factory can generate for manufacturers embracing it.
Due to limited awareness around smart manufacturing, most firms are still unclear about the impact that they can achieve through targeted investments.
In an interview with ETCIO, Ashish Nanda, Partner & Supply Chain Leader, EY India, explains what tech and business leaders should keep in mind while operating a smart factory.
“There seems to be a clear co-relation between the success of digital initiatives and top management’s understanding and commitment to these initiatives,” said Nanda.
What is the key consideration that business and technology leaders need to keep in mind while operating a smart factory?
The key consideration for technological leaders is whether or not digital systems with their improved computing capabilities can process large amounts of data and show real time status of raw materials, work in process and finished goods that helps in better forecasting, planning and execution.
Companies would need to work out the compatibility and integration of Information Technology, Operations Technology and the analytics platform for the successful implementation of a smart factory. Business and technology leaders need to understand how the technology will evolve and how they should integrate it with current operations to stay competitive.
Benefits of smart factory extend into associated functions other than manufacturing. How can its benefits be maximised?
The technologies and benefits associated with smart factory extend into other associated functions – product development, planning, procurement, and material movement in a seamless connected manner. For reaping the benefits, supply chains and other systems must connect with those of suppliers and customers.
Usually the human aspect gets ignored in the pursuit of technological revolution that later manifests in sub-optimal results. Companies need to invest on upskilling and cross-skilling the workforce. This involves hiring the right people, with the right skill sets and qualifications for the job, and managing them to ensure continuous productivity.
What role do cybersecurity and having a strong operational excellence program play in a smart factory?
Paying attention to IT security is very important for a smart factory, as it is one way to reduce business risks. Thus, management must invest in cyber security measures that will cover all aspects of the business, not just the technical or manufacturing side.
Having a strong operational excellence program would be vital for success in digital manufacturing. Analytical models need stability of inputs and processes to predict the outcomes and autonomous systems can only work in a very precise and predictable world. This insight has a significant implication and companies need to give enough attention to operational excellence initiatives while embarking on a digital journey.
What role do data and algorithms play in enabling a successful smart factory?
Current factories are characterised by fragmented systems, varied data sources without real-time information. As companies have understood the importance of data, most of them have started using sensors and wireless technologies to capture data from both new and traditional sources, ensuring data is constantly updated and reflects current conditions.
The key is how this real-time data is captured from production systems, maintenance systems, quality systems, process systems and processed to get actionable insights, thereby enabling decentralized decision making. Thus, manufacturing heads can anticipate and act before issues or challenges arise, rather than simply reacting to them after they occur.
Algorithms will enable organisations to manage loads of data generated, analyse and act upon it in varied, feasible sophisticated ways resulting in improved performance and manufacturing efficiencies.
Along with data, there comes a responsibility to protect it. Considerable measures need to be taken to protect all kinds of data. Also, analytical models need to seamlessly integrate with production processes assuring no latency and no compromise on production safety.