A good percentage of MSMEs are using various components of Industry 4.0

A good percentage of MSMEs are using various components of Industry 4.0

An interview with the Manufacturing & Process Consulting Practice team of Frost & Sullivan about future ready factories.

In December 2016, the 13th edition of the India Manufacturing Excellence Awards (IMEA) came to a spectacular close following the recognition of the best manufacturing companies in India. It was organised by Frost & Sullivan in association with FICCI and on the occasion, Nitin Kalothia, Director, Manufacturing & Process Consulting Practice, Frost & Sullivan said, “Manufacturing is the key driver of economic prosperity and creates more wealth than any other industry. The current challenges of low demand, increasing raw material and labour cost require organisations to adopt advanced manufacturing practices to become efficient and remain competitive. Adoption of right technologies to take companies to the next level of performance, efficiency and quality will be crucial to sustenance.” Encapsulated here are some of the views on this topic expressed by the team of Manufacturing and Process Consulting Practice:

How would you define the concept of a ‘future ready’ factory?

A factory which is identifying, modifying and implementing solutions to improve fundamental management control system, leveraging technologies to improve response along with accuracy rate, and encouraging the creative mindset to embrace change, is a ‘future ready’ factory. In today’s context, people are refusing product as a stand-alone proposition and are looking for complete service offerings to fulfil their requirements. For example, instead of buying individual pressure gauges people are now interested to avail the integrated pressure monitoring service as per their specific requirements. This ‘servitisation’ – the delivery of a service component as an added value, when providing products – of product is forcing organisations to redefine their values and offerings. The capacity to envision and interpret a conceivable, future state of customer requirements is the key challenge.

Constantly growing and competitive marketplaces are creating multiple choices for customers. It is becoming increasingly difficult to stand on a traditional value offering in a disruptive marketplace. In order to fulfil customer expectations, manufacturing in future will be completely different as compared to what it is today. A traditional management approach and mindset will not sustain in future. Organisations will transform into smart organisations where an integration of physical infrastructure, intellectual assets and technology adaptation will enable them to produce customised products with lesser lead time and enhanced value proposition.

How does this align with the concept of Industry 4.0?

Two interesting characteristics of evolution are “it’s slow but relentless” and “often people perceive the change when it’s completed”. The fourth industrial revolution (Industry 4.0) has already begun and all the organisational processes are transforming into a digital environment. This environment consists of cloud computing, big data, augmented reality, machine learning, Internet of Things (IoT, and other new and innovative technologies. Data is being generated by every cyber, human and machine around us. By leveraging these data, Industry 4.0 is helping us to manage, interpret, and in autonomous decision-making process. In the future, manufacturing and industrial facilities must be smart enough to evolve over time and fulfil the need of innovative product development, flexibility in production schedule, short delivery lead time and never-ending customer expectation. Big data, computation power, connectivity (IoT), and cyber-human-machine relationships are working together to facilitate the ‘intelligent manufacturing value chain’, which is known as a ‘future ready’ factory.

Apart from multinational OEMs in India, do you see this concept getting accepted in MSMEs as well?

Absolutely! In the past one year, we at Frost & Sullivan have not met a company head who is not excited about Industry 4.0. Already, a good percentage of MSMEs are using various components of Industry 4.0 in a fragmented manner and they are also enjoying partial benefits. Robotic automation, big data analytics for enhancing customer satisfaction and creating new value offerings are gaining popularity across MSME segments. The relentless pressure to improve performance and competitiveness are encouraging MSMEs to expand the scope and implementation of Industry 4.0. Change is a wonderful thing; it brings opportunities along with constructive challenges. To ensure continuity, all companies have to embrace change.

What are the challenges that manufacturers face to adapt to the technological demands of the future?

In this data-driven ecosystem, organisations are facing challenges with data security and IT infrastructure. Keeping the confidential data safe and at the same time leverage big data for intelligence amplification or use technology such as cloud computing to stay ahead of the curve are some of the key challenges. For future ready factories, manufacturers need future ready and digitally skilled workforce. Smart factory demands manufacturing subject matter experts who are flexible to learn and utilise new technologies. As mentioned earlier, Industry 4.0 has many components and each one is important to transform the vision into reality. The main challenge therefore lies in the identification of requirement, drafting the solution and implementation of the action plan. An adaptation of improper strategy or inappropriate technology can jeopardize the entire initiative.

How will this help bring about cost-effectiveness in operations and enhancement of quality?

Imagine a situation where operation managers are not constrained with minimum lot size or high changeover time. Yield improvement, utility cost reduction, real time deviation management are common benefits of Industry 4.0. In the maintenance space, a transformation from preventive maintenance to predictive maintenance will lead to reduction in maintenance cost, reduction in spare parts consumption, reduction in spare inventory level, operative cost reduction, higher up-time etc. Big data analytics is helping us understand the root cause of complex problems. We are analysing issues more intensely than ever before and that too in a time-effective manner. Autonomous process control, machine learning for predictive quality management has also been used in solving quality challenges and to achieve competitive advantage.


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