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BUSINESS AND TECHNOLOGY INSIGHTS

Driving real-time dynamic scheduling with Digital manufacturing

 
April 7, 2016

The first question manufacturers need to ask themselves before expecting any benefits from real-time dynamic scheduling is whether they have the right tools and technologies in place. This will save them much disappointment, and of course costs, at later stages.

Industry 4.0 has arrived with a bang

Industry 4.0 is a lot more than a buzzword. At its core is the interaction of cyber-physical systems fueled by the Internet of Things (IoT). It involves the successful integration of hardware components with advanced software applications to create feedback loops that enhance decision-making at the factory floor level. Industry 4.0 is, in fact, reshaping manufacturing, driving a shift from simple automation of tasks to an interconnected, intelligent digital environment that leverages large data volumes and sophisticated computational power

Digital manufacturing technologies not only help improve productivitybut also allow customization of products, enabling you to meet the diverse requirements of customers and giving you an edge over the competition. So, how evolved are these technologies? While we may still be scratching the surface, expect them to evolve rapidly in the years to come, particularly in the context of Industry 4.0 the fourth industrial revolution.

Taking manufacturing operations to the next level

Wont it be wonderful if you could predict your production floor outcomes, in near real-time? Well, Industry 4.0 can help you do just that, and a lot more. By simulating discrete events on the production floor, and factoring in additional data and constraints pertaining to workflows, digital manufacturing systems help optimize production throughput and effectively utilize resources in the production environment. Undoubtedly, the result is a marked improvement in the overall floor productivity.

Aside from monitoring equipment to pre-empt failures, simulation systems can also solve complex problems that involve diverse product variants, handle complex process interactions, eliminate the need for manual intervention, and reduce risks due to variable input and output conditions. Simulation systems can, therefore, prove immensely useful for production planning and dynamic scheduling. Using such a system, a plant manager can better plan production capacity based on the demand pattern, existing inventory, and availability of personnel and resources.

A leading ship building company we worked with witnessed notable productivity improvement by implementing a dynamic scheduling system. Using a combination of CAD, manufacturing process management, and MS project planner, dynamic plant performance data was captured from connected equipment. A manufacturing process simulation tool used this data to generate optimal scenarios with regard to asset utilization, time and cost optimization, and so on. This not only helped the operations team reduce planning time by 30% and improve space utilization and crane scheduling by over 20% but also allowed the senior management gain enhanced visibility into plant operation at all times.

While simulation systems are sure winners, at times, they can fail. Despite extensive predictive analysis and planning strategies, real-world scenarios can considerably differ from the virtual ones. Well, like all failures, these also bear some good results. Such variances, if closely tracked and fed into simulation systems, can notably improve the system performance. Simulation systems will use the new set of data points to recompute schedules and adjust future implementations for greater accuracy. And they wont disappoint you.Here is a look at how dynamic scheduling can boost throughput.

End-to-end system integration will be the stepping stone to success

Manufacturers are verymuch watching out for further progress in Industry 4.0. While the focus in the first leg of digitization was on simulation-based implementation for planning, scheduling, and production, it is hoped that manufacturers will now have a better macro and micro view and control of processes. This will be fuelled by the availability of exponential technologies.

The integration of end-to-end systems such as product planning, launch, and sales, all the way through to distribution and retail services is an important goal for the future. In the same vein, evolving technologies will enable facilities to connect with each other, sharing information through the cloud, irrespective of their locations. This communication network will help drive a transformational industry model where any and every data point will have a profound impact on a manufacturers strategic business decisions.

The ability to obtain insights into different control parameters will provide significant benefits to manufacturers, but most importantly, it will allow personnel to focus on high-value activities such as product development, innovation, and research.Based on our engagements with leading global manufacturers, we believe that this area will see considerable traction in the coming times. What do you think? What more will Industry 4.0 bring to fore? Will organizations need to reorient their operating models in the wake of these changes? If so, how?

Keep following to explore more about digital manufacturing solutions.

Ravi Govindaraju is a Domain Consultant with the Engineering and Industrial Services (EIS) business unit at Tata Consultancy Services (TCS). He has more than 28 years of experience in areas such as methods planning, NC technology, digital manufacturing, facility and resource planning, new plant introduction, quality engineering, industrial engineering, and value engineering. Ravi has authored about six research papers in leading publications, and is a member of the Institution of Engineers, India; the Fluid Power Society of India; the Aeronautical Society of India; and the Indian Value Engineering Society. He has a Masters degree in Machine Tool Engineering from the PSG College of Technology, Tamil Nadu; and an Honors degree in Mechanical Engineering from the University of Madras.