Manufacturing industry, in the last half a century, has witnessed perceptible growth and significant benefits from Lean systems. It aimed at operational waste elimination only to hasten value-flow and exceed the ever-increasing expectations of the customer, society and employee. However, with the increasing size and complexity of operations in the current supply chain, many companies have started finding Lean techniques alone, not enough to address the growing competitive business pressures. This new need has driven the merger of physical and digital worlds in the form of Industry-4.0 (I4.0) and then getting embedded into the Lean manufacturing systems.
Under the umbrella of I4.0, with the explosion of large production volumes / scales, operational digitization, interacting machines, growing automation, powerful data analytics and swift data-driven intelligent decisions, lean continues to be the critical foundation of growth sustainability. The two together are transforming manufacturing operations to become more efficient and effective and thereby making business more profitable. The significant I4.0 components are Industrial Internet of Things (IIOT), Big data analytics (BDA), Additive manufacturing (AM), RS (Robotic systems), Augmented and Virtual reality (AR & VR), Cloud computing (CC) and Cyber-Physical Systems (CPS). Â
Under the Lean domain the much discussed eight manufacturing process wastes with the acronym DOWNTIME, are: Defects in output, Over-production, Waiting, Non-utilization of human talent, Transportation not adding value, Inventory in excess, Motion not warranted and Excess-processing. A deep analysis indicates that the digital world of I4.0 can significantly reduce each of these eight wastes significantly, thereby improving leanness of systems.     Â
Creation of products that have defects / errors do not meet customer requirement and is a tangible waste demanding rework, rejection and causes customer dissatisfaction. To ensure first time right, digital data captured from sensors in the inter-connected machines (IIOT) will enable identification of the source of error and trigger fixing the root cause. This enhances the process capability to move towards six-sigma quality levels. The vision camera technology of I4.0 are comfortably preventing the error moving to the end-customer. The real time data collection, application of analytical tools and computer algorithm of the BDA component can provide deep insights and facilitate quick decision-making in technical processes to reduce defects.  Â
Production output from work-centre, not synchronized with supply and demand, result in over-production. The visibility of instant real time data on excess output in the e-value-stream compel the workers and decision-makers to swiftly respond appropriately and prevent the push to the next work station. The inter-connected hardware in the IIOT system along with machine layouts prevent the production system from producing more.
Work-station process imbalances, bottlenecks, breakdowns, absenteeism, defective system behaviour and ineffective planning lead to the waste of waiting. The visible digital processes nudge the server to continuously reduce the lead time. The e-andon system provide signals for appropriate actions. The AM component of I4.0 has accelerated the manufacturing in smaller lot sizes, no material waste and thereby responding quickly to customer needs. The Predictive and Condition-based maintenance in I4.0 facilitate asset maintenance planning and thereby reduce the costly waiting time. Digital process data of material flow would stabilize the Just-in-time process and move towards zero waiting. The readily available data and BDA use simulation tools quickly to arrive at an optimal process flow design with zero-waiting.       Â
Non-involvement of people and not utilizing their full-potential is a major waste. The accountability and ownership from application of e-VSM for continuous improvement by the value stream owner(s) would lead to improved people engagement and value-added delivery. Innovations and improvements in the new domain of Lean – I4.0 will provide high level of fulfilment. Use of Cobots (RS component of I4.0) is replacing the monotonous repeatable, dangerous, dirty and tough jobs of people by more valued-added, creative and innovative ones.       Â
Non-linear flow, backtracking and unwanted intra and inter plant transportation of material is a waste. Location and shop floor layouts are the largest contributors to this waste. The digital data from the e-VSM is used for simulation and arrive at the optimal material movement route within and outside the plants. AGVs (Automated guided vehicles) and AS & RS (Automated storage and retrieval system) elements of the RS component in I4.0 are playing a key role in easing the internal transportation systems in complex shop floors.Â
Ineffective production planning, push systems and instability in value streams result in inventory related wastes. This is the most significant waste in the manufacturing system. The real time data availability across the digital value stream, including the customer-end consumption, has the capability of triggering decision-maker to act and thereby prevent excess inventory in the supply chain. Application of RFID, e-kanban systems, smart sensors, Big data analytics has taken inventory management in value streams to the next level. The CPS component of I4.0 connects various physical machines to the central processing unit and thereby provide access to data and adaptable which, in turn significantly reduces the in-process inventory.      Â
Sub-optimal design of layouts, poor ergonomics and ineffective workflow within workstations lead to unwanted motion of material and people leading to waste. Movements related to work-stations using AR & VR data to arrive at an optimal layout of the work-centre always delivers useful output in motion-waste reduction. Automaton related applications of cost effective COBOTS have improved productivity and product reliability hugely.Â
Excess processing like 100% inspection, over-designed process and stringent drawing specifications not adding value to customer lead to waste.
The product life cycle data from the CC component facilitates in simulating and then optimizing the critical design specifications to prevent and over design. The real time digital data provides online process-capability of work stations and throw-up a lot of insights to technically trigger improvements in process becoming more robust and thereby preventing unwanted inspection.  Â
Lean is a well-established approach for value flow improvement, which has now got turbocharged by the digital world of I4.0. Digital lean has opened a huge Pandora-box of improvement opportunities in the complex manufacturing value chain today.
Dr. Ravindra Ojha is Professor of Operations at Great Lakes Institute of Management, Gurgaon.