Fostering Industrial Growth by Digitalisation
Published on : Sunday 06-09-2020
In this second installation of a multi-part series, Jasbir Singh explains how digital transformation is impacting companies, strategies and business models.
AI-aided digitalisation, historical data-driven planning, accelerated production, quality manufacturing, and smart maintenance are the key for success in industry today. The evolution of new digital industrial technologies adopting Industry 4.0 (fourth industrial revolution) is transforming processes. It is now easy to gather and analyse data across machines, enabling faster and more efficient auto retuning that sets parameters for processes to produce improved- quality goods at reduced costs. This technological revolution will improve productivity, shift economics, and modify the workforce profile which will ultimately enhance the competitiveness of companies and their businesses.
The growth of business by advance automation and modern data technologies is powered by the Internet of Things (IoT), cloud storage and computation, advanced computers, robotics functions and control, powered by Artificial Intelligence (AI) and people. The seamless integration of application software, data and operating people increases the speed, reliability and flow of information between all systems of a manufacturer to increase productivity and no wastage. Industry 4.0 targets to increase cohesiveness among sections, departments, functions, across business including seamless networking from supplier to customer. This will enable fully automated systems in the entire value chain and all data can be parked and retrieved easily as and when needed for further improvement or analysis.
The technologies connected by Industry 4.0 are a combination of various new and existing technologies but the integration among them is seamless and quick to respond to the external and internal change in command. Parallel use of virtual and physical digital data during processing in machine software for hardware production makes it more efficient and faster. The principles used here are Virtualisation, Interoperability, Modularity, Decentralisation, Real-time capability and Serviceability.
Technological upgradation using Industry 4.0 mainly encompasses IoT, AI, digitalisation and integration of data and workflows, additive manufacturing, remote monitoring, multi and inter disciplinary engineering, and automation of controls through machine learning and predictive analytics.
Gathering and extensive evaluation of collected real time and historical data from multiple sources such as production equipment and its control systems, enterprise information, supplier and customer management systems will become the foundation to support real-time decision making in logical framework.
The application software used to drive the process is simulated by creating soft inputs and outputs in the lab before uploading to the machine for perfection of product output and running the machine with full capability from day one without loss of time at site. Setting for other recipe/product can be easily tested offline, simulated, before the physical changeover and with this operator optimises the machine setting time and runs in confidence to produce quality product at no risk of defect. Simulation becomes the part of real world where virtual model shall be the mirror image of physical implementation at site.
Industrial IoT or IIoT platform is the network for connecting front-line industrial processes with back-end information systems. It shares data between machines to digital devices and company network. This includes plant hardware and application software of systems to securely access, monitor, analyse and enable manufacturers to develop innovative applications for business to create value. Fundamentally, IIoT Platforms are tools for improving connectivity, control, and analysis of data in industrial environment to design, manufacture and link to customer support digitally and providing physical services. Using IoT and connecting Cyber-Physical Systems (CPS) to communicate and collaborate in real time with internet services enables us to connect both internal and cross-organisational services in the value chain to stimulate our role and function for the growth of organisation.
IIoT is extensively used for direct inventory management from supply to finished product – warehouse in industry or hospital medicine inventory – which gives real time information of stock, movement pattern, expiry date, high and low alarm through sensors without physical stock checking. The integrated inventory management system enables companies to achieve cost-savings in its supply chain and procurement management. IIoT significantly improves operation, increases system efficiency, reduces variable costs and provides information on real-time basis across the supply chain. This information helps optimise inventory of raw materials and finished products by calculating the in-line production speed and products in pipeline of supply chain.
The development of advance information and communication technologies, commonly defined as CPS, integrates people with real-time information and data, stored data bank of machines and equipment for analysis, interpretation, and decision making across the manufacturing operation. This leads to produce quality output and provides tractability at all platforms by having high level of data security. Every stage in the manufacturing operation is digitally connected and lot of data generated, which is used in machine PLC and requires robust cybersecurity and the manufacturing machinery, computer systems, data analytics, the cloud and any other system connected via IoT, should be protected.
In next generation manufacturing the integrated use of robots/robotic functions in machines becomes the part of total enterprise system. The role of robot is to assist the machine and operator to produce defect free items with high productivity at lower cost and capture the data in parallel, stored, displayed in right format for future planning and used for quick control
parameters. These robots increase the capabilities of machines manifold in greater range of work process. The processes become smart and intelligent to manage the machines using digital sensors communicating with touch panel/computer interface to configure, operate, data collection and health diagnostic.
Additive manufacturing technique brings value to produce complex geometrical parts and structures. 3D printing is commonly known as additive manufacturing for producing rapid prototypes it has now evolved to replace a number of different technologies. The evolution of 3D printing has attracted a rapid growth in the number of companies to produce functional prototypes and parts in shortest time frame. The manufacturing process adopts the composition of successive layers of material on top of base layer one by one. It is widely used for prototyping construction where products with different materials are produced to check durability, consistency, capacity, limitation, life and its contact with other materials. As the potential applications perceived for 3D printing are increasing, companies are finding ways to create new business models and opportunities. Wide models of 3D printing surfaced during current industrial environment where even houses and high-rise multi storey buildings are in the developing stage with this technology.
In advanced digitalisation under Industry 4.0, machines communicate with each other, smart sensors, controllers, robots, signature curve created by machine learning and recipe requirement, what we call Smart Production Chain (SPC) by linking different sub modules. Industries integrate the real world with virtual one and enable machines to collect online data, analyse it, and make decisions. This will allow field devices to communicate and interact both with one another and with centralised controllers, as necessary for machine operation. It will also decentralise analytics and decision making, enabling real-time responses.
The use of autonomous equipment, with robots and cobots is introduced in manufacturing process as we look forward to increase output and high efficiency. Autonomous robots and cobots increase production speeds, improving productivity, creating a more efficient work flow, and reducing overall costs. Cobots are next generation robots that are designed to work along with workers in sync. Cobots and more like automated assistants to operator that are force multipliers for individual worker on the machine operation.
The factories of the future are being developed on digital platforms where people and machines are collaborating together in everyday work with that the manufacturing technologies are continuously becoming more efficient. Factories are increasingly automated having processes using innovative concepts of intralogistics where production and logistics processes are skilfully linked.
AR applications in the manufacturing industry have been developed for multiple purposes. This include process monitoring and control real-time evaluation of plant layout, plant and machinery maintenance, plant and building construction, as well as for enhancing industrial safety. AR technology is well-suited in industrial environment, for workforce training on product manufacturing and machine maintenance, improving product quality and improving production-to-market time lines though pre-production simulation or virtual testing of individual product and integrated assembly line at every stage of manufacturing.
1. Self-assessment of the difference between current status and target output, and set a goal to close that gap. Prioritise the important factors to the company which align with the company’s overall strategy.
2. Initiate a pilot project to ensure first success in steps or direct result. This will pave the path to persuade leadership for overall implementation and secure planned investment. This is learning phase requires cooperation with internal experienced operators, external experts for exchange and learning.
3. Based on the pilot test, more information are gathered to know the outsource resources and skillset needed to achieve the goal.
4. Exiting data analysis and its right use will be most crucial to achieve the set goal.
5. Use expert advice/guidance to formulate the implementation strategy and maintain time line at least for the vertical deployment. Horizontal deployment will be easy by using the learning and data of running system.
Whenever a company decides for sustained growth by way of technological upgradation it starts with the implementation of Industry 4.0. It requires a systematic assessment of complete value chain in existing system and addition/integration with new machines. In case management wants capacity augmentation by adding new lines, they need to look into possible cost cutting in the following areas:
1. Plant and Design layout
2. Shared utilities & interconnection
3. Production technology, and
4. Engineering.
Vertical value chain model shall be used for complete automation at every level for seamless integration and less dependency for physical checking or human intervention. It reduces the mistakes and cost to quality (COQ). The project implementation needs a four step modular approach, which itself has many sub critical steps to understand and requires further detailing. Any modernisation project in existing line shall be implemented in one machine as pilot project. The pool of skills from operators, supervisors and other resources available in the organisation is to be identified and assigned as project team. Defining and planning are most important to make the project successful. It requires a detailed study and proper script with flow chart and to be given to top management for their approval before implementation. This is important step to follow even if the team has in principal approval. This fetches management commitment and involvement to support in case some additional facility or resources are required during implementation. New line with sophisticated machines, highly automated system having smart sensors and well digitally connected to all machines by secure network with fast flow of information can be developed. This developed system shall be simulated multiple times and adding new features as and when found necessary keeping it well within the budget. The final system design requires to be shared with existing machine operators before final approval from management. The long experienced operator and technicians gives valuable feedback for further improvement.
Once approved by management team the assigned will take full ownership for its successful implementation and taking pride in innovative design. This group of people not only properly implement but easily maintain as their knowledge goes high for autonomous operation and maintenance. All different levels in vertical value chain can be connected with Blockchain during planning phase itself.
Digital transformation has a profound impact on the company, affecting its strategy, talent, business model, and even results due to the ability to interact, connect, share, and initiate perpetual decisions which are extremely convenient for leaders.
(Part 1 of this series had appeared in July 2020 Digital Edition of Industrial Automation)
Jasbir Singh is an Automation Expert with experience in Factory Automation and Line Automation in a large production house. He is an Implementation Strategist, Business Coach and a regular writer on automation, AI, robotics, digital technology, network communication, IIoT, wireless communication, blockchain and use of advance digital technology. Jasbir has a long association with industry to improve factory automation in production lines for productivity improvement in India and overseas by advising and also transforming into digital platform by use of AI. May please add comment as Chart not to be copied in any form without written permission from author
