The automotive industry has gone through several transformations over the years and the same has impacted manufacturing planning. Automobile manufacturing always focused on producing vehicles faster, better and cheaper by conceiving different methodologies. The earliest reference to manufacturing productivity is the Ford Assembly Line concept in 1911. The robotics revolution was triggered by Unimate from General Motors, the very first industrial robot in 1961. Robotics, Artificial Intelligence and the Internet of Things have all become part of a new industrial revolution.
Over this evolutionary cycle today, the smart factory requires heavy investment in connectivity & automation, advanced algorithms for managing workflow, scheduling jobs, creating supply side and customer side information sets. High investments are also required in technologies that enable virtualisation of design & testing to achieve faster time-to-market and lower physical prototyping & testing costs.
Industrial revolution I, II, III, IV
The first industrial revolution started with the introduction of the steam engine innovation that enabled large scale manufacturing of goods, such as textiles, coal, paper, etc. The second industrial revolution can be attributed to the introduction of electricity and it enabled the mass production of goods. The third industrial revolution was all about computers. The fourth industrial revolution – also referred to as Industry 4.0 – is the ongoing transformation of traditional manufacturing and industrial practices combined with the latest smart technology.
Digital manufacturing is one piece of this jigsaw puzzle and is a bridge between the third and fourth industrial revolution. Many organisations do not possess sufficient technology and automation to migrate to Industry 4.0.
Digital manufacturing in automobile industry
The definition of digital manufacturing is multidimensional and varies from industry to industry. Digital manufacturing is the key enabler of Industry 4.0 and can be defined as a computer-based system comprising simulation, three-dimensional visualisations, analytics & various collaborations of tools to create product & manufacturing process definitions simultaneously. A digital manufacturing system allows manufacturing engineers to create the complete definition of the manufacturing process in a virtual environment and develop the digital factory.
The concept of digital twin, which is a virtual replica of the product through its lifecycle, is also gaining importance in the industry. Digital manufacturing is a proactive approach to develop, simulate and deploy the real manufacturing environment to study manufacturing impacts & challenges.
The focus of digital manufacturing revolves around the four Ps – product, process, plant & people. Digital manufacturing enables one to formulate and develop upfront planning on how to deploy the product, process, plant and people. This enables one to clearly define the targets for scaling the production process from one plant to another.
Digital manufacturing can also be defined as ‘simulate all the processes of production using 3D models of the product & resource using computer’. The objective of digital simulation is to optimise the four Ps. The strongest benefit of digital manufacturing is proactively working on ‘what-if simulation’. We can know various results based on alternatives before the actual manufacturing is completed. The computer-based simulation can save the cost of real try-out & danger. Various digital manufacturing solutions are used in the automotive industry in different domains. A portfolio of tools and solutions are detailed below (Not limited to the below).
The digital manufacturing domain includes, but is not limited to virtual prototyping, ergonomics analysis, robot simulation and OLP, tolerance simulation, digital quality simulation, discrete event simulation, virtual NC simulation, forming simulation, casting simulation, moulding simulation, digital process planning, digital inspection and so on.
Why digital manufacturing?
Traditional product development is focused purely on the product design and aesthetic development. Prototyping & manufacturing processes are followed at a late stage. This often causes long lead times if the design cannot be manufactured. The introduction of simultaneous digital manufacturing ensures that the product designs are verified early. In many organisations, the physical prototypes are replaced by virtual prototype and digital manufacturing evaluations are conducted. This reduces the overall product development time as well as the cost of physical prototypes. The key advantages of digital manufacturing are as follows –
Faster product development – Less time due to all virtual manufacturing is conducted in the digital world
Low prototype cost – The reliability of virtual prototypes enables one to go for less physical prototypes
Variant & complexity management – Multiple variants & DMU are conducted for complex products
Manufacturing feasibility – Simulations for moulding, casting, forming identify manufacturing bottlenecks, if any
The latest trends & technologies from the digital manufacturing world
VR, AR, MR Technologies
Though VR/AR technologies have been available in the market for some time, the use of these technologies was limited due to –
Heavy product data in the automotive industry
Pre-process of CAD data for VR/AR platform
Internet bandwidth for intercontinental collaboration
Large and clumsy hardware to operate the environment
With the introduction of lightweight CAD formats, high internet bandwidth, lightweight hardware, VR/AR technologies are getting more and more popular in the simulation domain. Many organisations are testing VR/AR applications and exploring the capabilities. The present penetration of VR/AR in digital manufacturing is roughly 5% of the overall simulations in the digital manufacturing domain. COVID-19 has accelerated the adoption of some of this technology. The virtual training of blue collars with VR/AR is gaining popularity for the management of new model introduction. VR/AR technologies have a potential to scale up in the simulation industry and become a daily used product & application.
Digital twin vs digital shadow
The digital twin is an active simulation aiming to run in parallel and interact with a physical twin. A virtual copy of a real product, process, plant or people constitutes the digital twin.
Digital shadows are abstracted traces captured by sensors/cameras of the real/physical environment. The data generated live is used for live dashboards, system monitoring, predictive maintenance, etc. More developments are expected in the digital twin and digital shadow domain.
Virtual commissioning is the latest trend picking up in digital manufacturing due to the COVID-19 travel restrictions. In virtual commissioning, highly complex manufacturing automations can be completely modelled in the virtual commissioning engine, with which the entire system can be virtually run, with Hardware in Loop (HiL). A functional digital twin interacts with physical hardware and simulates the production environment. The systems can be tested virtually from remote locations and verified for the performance. The entire production performance can be verified and validated even before starting the assembly of the actual solution, line or machine. The nascent stages look promising & very complex systems can be tested and buy offs can be done without the need for travel.
Intelligent & adaptive machining
The methodology in CNC machining has progressed over the last few years. The tool path generation, cutting feed, axis synchronisation and more can be simulated & virtually tested with machine beds. The latest technology involves intelligent machining where feed rates can be kept constant with an adaptive tool path. Adaptive machining optimises the tool feed & path and provides greater productivity & quality. A similar approach is also followed in forming, moulding & casting simulation in the pre-processing domain.
Future research areas in digital manufacturing
Data-driven digital manufacturing would be one of the key pillars of future digital manufacturing. Today, very few organisations are able to use their legacy data in digital manufacturing. This is attributed to the multiple legacy systems, challenges in data migration, expensive transformation process. However, once these data are structured and organised, it can be used for digital manufacturing to a great extent.
Today, 90% of digital simulations are executed manually. Thus, digital manufacturing simulations are human-intensive and consume time in processing. It also gives a potential opportunity for automating the simulations and reduce the engineering hours spent on the project. PLM systems which can integrate product–process interactions in live and automatically detect & report as in the case of RPAs are the future to reduce the dependency of human effort.
AI-based digital manufacturing solutions are also getting evolved and tested for various PoC in different industries. The future of digital manufacturing is unpredictable, but we expect more and more organisations to utilise data as the foundation for the future.