Manufacturing processes and supply chains are getting increasingly more complex, while manufacturers face constant pressure to reduce their time to market. In an automotive supply chain, for instance, demands for new products can require tens of thousands of components to come together at the same time from different origins, using different modes of transport, and throughout different continents. The assembly line must then be ready with all possible combinations of people, process, tools, equipment, and technology to assemble and transfer new products to end consumers through a variety of channels. Digital-twin technologies can help overcome these challenges by simulating manufacturing processes, thereby allowing companies to address a variety of scenarios and changes that can boost production cycles, keep them ahead of potential bottlenecks, and improve efficiency and throughput.
Modern Manufacturing Challenges Requires Modern Solutions
One of the key concerns is reducing the time for new-product production and delivery. But when introducing a new product to the market, manufacturers and planners must address several key questions before changing their capital-intensive physical infrastructure:
- What happens to the existing production line if a new product is introduced? Will production targets be impacted?
- Are there any bottlenecks in the current system, and if so, where?
- Will bottlenecks be solved by increasing the number of machines, and if so, at what stage in production?
- Should the layout or material routing be changed? Or, should there be changes to the batch and buffer sizes within the line?
- Is it possible to optimize the available operators and AGVs or forklifts? If not, how many resources are required and where? Or are there any other criteria that need to be evaluated?
What is a Digital Twin?
All of these issues can be quickly analyzed using a digital twin, as manufacturers are increasingly realizing. A digital twin is a complete digital simulation of the manufacturing process. As of 2020, the market size for digital twin had exceeded $5 billion, and it’s expected to grow at least 35% by 2027. The growing adoption should be no surprise; digital twins can analyze many permutations and combinations, with simulations for all of a plant’s technologies and IT systems. These simulations provide the best and most-optimal recommendations without affecting the current manufacturing environment.
Tomorrow’s plant efficiency can be enhanced by looking at today’s challenges. A digital simulation helps a manufacturer validate changes in the production process before making any costly adjustments that may not be necessary. Digital simulations enable exploration of different what-if scenarios, testing different equipment make and models, varying the location of physical assets within the layout, changing the process flow, and creating alternate MHE routings, for example. These scenarios can all be solved to optimize the manufacturing process, plant capacity, and improve throughput of new or existing facilities.
The simulations can also identify problems before they occur and predict the future outcomes in unforeseen scenarios. This enables a manufacturer to improve overall equipment effectiveness, reduce waste, enhance product quality, optimize process flow, increase throughput, and eventually improve plant operations.
An Example of Digital Simulation Improving Efficiency
Example: Wipro worked with an Indian automotive components manufacturer to overcome challenges on the manufacturing floor. The manufacturer wanted to increase the productivity of the operations, optimize the space floor by adding new machines or equipment, improve process flow, and optimize the MHE.
The shop floor activities and existing process were replicated within a digitally simulated environment. The ability to run scenarios before commitment identified several improvements: group products and variants based on processing and routings, identify and reduce gaps between workstations, rearrange the machine cells, and gradually shift to MHEs to control and transport in the shortest distance. The available shop floor space increased 35% by adding new machines, there was a 25% savings in material movement and reduction of MHEs, and overall cost savings were approximately 20%.
Today’s manufacturers are facing a host of new challenges, and there is a need to introduce more efficient and adaptive technologies to tackle these issues. Digital simulation provides this capability, enabling engineers to generate what-if scenarios and run simulations to validate changes before making expensive capital investments. Moving forward, digital twins will be an essential part of manufacturers’ efforts to reduce new-product development times and costs while optimizing production and distribution.