The Road to Smart Manufacturing with Digitalisation
Published on : Wednesday 03-01-2024
How digitalization is helping companies to rapidly scale up on the factory automation front.
The process of automation in manufacturing has been a continuous one ever since the first industrial revolution. However, the internet played the role of a catalyst in first hastening the pace, and next, unleashing digitalization that is now revolutionizing manufacturing and much else. Industry 4.0 ushered in the era of smart manufacturing by bringing together all the emerging technologies on a single platform, making the transition from traditional manufacturing to the smart factory environment much easier. In the process, it has also leveled the field, bridging the technology gap that traditionally existed between the large manufacturing conglomerates and the Small and Medium enterprises of SMEs.
As Sureshbabu Chigurupalli, Board Member-Director, Balasore Alloys Ltd, and one of the participants in this discussion says: “Many modern businesses now rely on automation in manufacturing to get products built faster, optimize workplace processes, and get orders to customers more efficiently. Automation in manufacturing refers to using technology and machines to perform specific tasks without the need for humans to intervene. The goal of automation is to increase efficiency, productivity, and accuracy in the production process, reducing manual labor and minimizing the risk of human error.”
At a time when there is a deluge of information freely available from various sources about the process of digitalization in industry, many companies are still undecided on the right course to adopt for the transformation. So what are the key aspects to consider for a typical company that wants to switch over from a traditional manufacturing process to an automated environment?
“The key aspects for companies to consider when wanting to switch over from a traditional manufacturing process to an automated environment start with defining what the company’s objectives are, such as increasing production to grow the business based on revenue forecasts or increasing productivity of existing assets and employees to be able to meet production goals for a lower cost,” says Craig Resnick, Vice President, ARC Advisory Group. “Within each objective comes a calculation regarding investments that need to be made to achieve those production or cost goals, which can include what technology, such as hardware, software, and services would be required; and based on those investments, what would be the expected key performance indicators and the return on investment,” he adds. As the primary analyst for many of ARC’s automation suppliers and financial services clients, Craig’s focus areas include production management, OEE, HMI software, automation platforms, and embedded systems.
Amit Saluja, Founder, and Managing Partner – digiXLT, an accelerator to help manufacturing industries, especially Small and Medium Enterprises, navigate through the digital journey, believes that manufacturing has become the backbone for the country and with growing demand in both domestic and exports, it has become imperative for enterprises to look for ways to produce more with consistent quality and that too at a lesser cost. “While manufacturers prepare for this transformation, they need to plan it as a journey and not look at it as a one-time setup. The start must be with building a digital mindset where management understands the applications of technologies on the shop floor and workers are open to using automated digital solutions. When it comes to assessing RoI to decide on adoption, both direct and indirect benefits and costs need to be considered. As this is not straightforward, a better way of getting confidence is to do deployments at a small level in the plant and scale later based on the benefits received. Another important aspect is technology adoption should be planned with long-term focus considering the company's future business objectives rather than trying to handle immediate challenges,” he suggests.
“Traditional manufacturing companies (such as in energy, mining, utilities, and manufacturing) struggle in setting bold aspirations, developing robust business cases, leveraging cross-functional capabilities, and devising effective deployment approaches to reap maximum value from automation initiatives. Building these capabilities could help those companies realize benefits at scale, improve customer and employee experience, and build a long-term competitive advantage,” says Shatam Bhattacharyya, Principal Business Consultant, at AI Transformation Consulting. As a seasoned business consultant with 11 years of experience in process transformation by leveraging AI, Shatam has prior experience in the BFSI, FMCG, and manufacturing industries spanning across multiple functions like supply chain, manufacturing, and IT services. According to him, the traditional manufacturing industry’s distinctive nature requires a tailored approach to achieve ambitious business goals and ensure sustainable processes and cultural changes. “First, the fragmented data landscape and complex legacy infrastructure have posed challenges for heavy manufacturing companies to adopt emerging technologies. Second, core manufacturing industries operate in a more risk-averse culture compared to other industries, sometimes contributing to distrust in the deep tech such as Artificial Intelligence, Virtual Reality, Augmented Reality, Blockchain, etc,” he opines.
While most experts are united in maintaining that rather than going the whole hog, companies should make a small beginning and then scale up, how scalable are automation and digitalization solutions for different sizes of manufacturing facilities?
“Scaling up digital transformation is a complex process that needs careful planning, management, and evaluation of the costs, benefits, and impacts of the solutions,” cautions Girish Ayya, Co-founder, of Avadhoot Automation Solutions Pvt Ltd. As a Technologist, Industrial IoT Evangelist, and Thought Leader, Girish is helping Indian manufacturing industries to achieve a digital transformation journey through disruptive technologies. Some of the factors that affect the scalability of automation and digitalization solutions according to his are the compatibility and integration of the solutions with the existing processes, systems, and machinery; the availability of resources like IT infrastructure, skilled workforce, and leadership; and the alignment and coordination of solutions with business goals, needs, and core values.
Sudhanshu Mittal, Head & Director Technical Solutions, Nasscom Center of Excellence – IoT & AI, Gurugram, also believes that scalability is critical to any automation activity. The tools – both software and hardware – should not become bottlenecks as the company looks to scale up its operations. Tools based on popular standards and open standards are the most preferable as those prevent vendor lock-in and provide the capability to work with different vendors in the future. “A large enterprise may use a tool like SAP or a high-end automation platform like PTC, but this may not be suitable for a small enterprise, both from the cost and tool complexity perspective. This makes the job of selecting appropriate tools more challenging for small enterprises. However most of the MSME category suppliers also try to follow open standards as much as possible, primarily due to demand from the customers so manufacturing players should try to prioritize those,” he explains. Having spent 25+ years in technical roles in different companies like HCL, Agilent, Marvell, Freescale, and Juniper among others, Sudhanshu Mittal has gained extensive experience in embedded domains in different verticals like networking, storage, printing and imaging, medical equipment, IoT, security, etc.
“Different manufacturing facilities have different needs and one has to understand the needs, be it the manufacturing process, the product profile, manufacturing resources, the customer base, the served market, and future plans. While the scalability would depend on the above factors, there is technically no limit to scalability with present-day technologies,” opines Ramnath S Mani, Managing Director, Automation Excellence. With over four decades of industry experience with companies like Rockwell Automation, Emerson Control Techniques India, and Emergys Software India behind him, Ramnath is also past President of IIT Kharagpur Alumni Foundation India and past Chairman of Pan IIT Alumni India from 2018-20. According to him, “What limits scalability is the vision of the top management and the approach it takes towards the selection of platforms, vendors, ecosystems and the technology. The prudent way forward would be to have a vision and an end goal and move towards it in steps and see improvements and stability in each step before moving forward. For this selection of the technology, the platform, vendor ecosystem has to be planned well in advance, consistent with the market needs.”
Whether a company goes for a total transformation approach or opts for scalable solutions, what are the initial costs associated with implementing factory automation and digitalization?
“The initial costs of implementing factory automation and digitalization can vary depending on factors such as the size of the operation, the complexity of processes, and the level of technology being adopted. It is important for businesses to consider various cost categories when planning for automation and digitalization,” says Sureshbabu Chigurupalli, who has achievement-driven professional experience in spearheading entire unit/plant operations to maintain continuity and match organizational goals at Balasore Alloys Ltd. He is leading and managing all plant operations with effective utilization of all resources and implementing industry best practices such as TPM, Six Sigma, Lean Management & other Business Excellence initiatives that contribute to improving productivity and efficiency. According to him, capital expenditures (CAPEX) include costs for automation equipment, such as robots, conveyors, CNC machines, and AGVs. Software costs encompass expenses for purchasing or licensing software like MES, ERP systems, or PLM tools. Integration costs involve customizing and integrating automated equipment and software systems into existing processes.
According to Craig Resnick, the initial costs of implementing factory automation and digitalization can vary widely. “The initial costs of adding some proximity sensors connected to a nano or micro PLC may cost less than $1000 to do an extremely simple material handling application, but when you are dealing with thousands of sensors, multiple PLCs and PACs networked together, AC drives, HMI/SCADA software, etc., the initial cost can rise to tens of thousands of dollars. The good news is that thanks to the modularity of factory automation and digitization solutions, a manufacturer can just spend what is currently needed and add to or expand the existing installed base as their needs change. This is especially true with most software thanks to software as a service, subscriptions, and cloud, where these initial costs for a small application could cost under $1000/month, but quickly scale to thousands of dollars per month depending on what applications are being added,” he elaborates.
Amit Saluja concurs with the low threshold of initial cost with the right approach. “When a manufacturer plans to initiate the factory digitalization process, the initial priority is to build the basic level of digital infrastructure. This means getting machine-level connectivity established that will enable the transfer of operations data and analytics capability for the specific application/use case where the manufacturer is facing challenges,” he says. However, once connectivity is established, there are multiple applications that can be deployed based on the priority areas of improving plant operations. While it is needed that all the machines in the plant should be connected and on the network, to feel confident of the benefits, initially it can be done for a small number of machines, say 5 to 10 critical process equipment. “This level of proof-of-concept solution for limited machines along with data analysis capability can be built with an initial investment of around Rs 10 lakh,” he states.
How does the adoption of automation and digitalization impact the skills required for the workforce?
“How companies navigate the technology world to sustain competitive advantage is the ultimate challenge for many CxOs of the core manufacturing industry. To be fair, this challenge has been persistent over the last decade. But the business implications are getting broader day by day with the advent of emerging technologies like AI, blockchain, etc. Companies realize they need to respond to this challenge, but they are struggling,” observes Shatam Bhattacharyya. Per him, it is also a challenge with enormous potential for those who get it right. Industry leaders in other industries like BFSI, Telecom, etc., have outperformed their peers with a deeper integration of technology across end-to-end core business processes. “During this journey, these industry leaders have prioritized workforce reskilling, building the right talent base, and improving technology adoption. Currently, heavy industries face a few challenges in their adoption journey. First, the core manufacturing companies have traditionally outsourced large technology transformation programs. They have emphasized building in-house competency in core operations. On the other hand, other industry leaders have leveraged a robust in-house Centre of Excellence model to embark on a transformation journey with emerging technologies,” he explains.
“The adoption of automation and digitalization has a considerable influence on the skills needed for the workforce,” says Girish Ayya. Based on some studies, the primary effects according to him are as follows:
The need for technological skills will increase, as the workforce will have to use, develop, or adapt new technologies in their work.
The need for soft skills, such as communication, collaboration, creativity, and problem-solving, will also increase.
The need for cognitive skills, such as data entry and processing, will decrease, as these tasks can be more easily automated.
The need for lifelong learning and reskilling will become more important, as workers will have to adapt to changing work environments.
For Sudhanshu Mittal, the skill requirement impact has two areas – first the required skills to manage automation and digitalization, and second, the skill upgrade for workers so that they are able to perform tasks that machines can’t do and prevent themselves from becoming redundant. “About automation management, the workers will be required to build digital and technical proficiency, as well as have sensitivity to the data being generated from manufacturing processes as the leak of digitized data is much easier than the traditional paper-based data. Workers will need to develop capabilities for data analysis. Regarding the second point about workers protecting themselves from getting replaced, this will require them to develop leadership and management skills so that they can guide the changing processes. They will have to develop soft skills as their role will become larger and may require more collaboration with team members and outsiders,” he elaborates.
What regulatory considerations should manufacturers keep in mind when implementing automation and digitalization with respect to safety and security?
“As we move towards Automation and Digitalisation, especially towards Cloud-based technologies, we have to be aware that cybersecurity breaches could be a threat. Safety and security form the basis of a successful implementation of Automation and Industry 4.0,” says Ramnath S Mani. “With a view to ensure operation and maintenance of the plant and associated equipment is improved with greater efficiency, safety, reliability and risk management, a number of Standards have been formalized through IEC, ISA, ANSI, ISO, etc. In the US, Homeland Security has set up formal standards for cybersecurity for manufacturing to avoid external threats. The Indian government is also working on similar lines to protect manufacturing,” he explains.
According to Sureshbabu Chigurupalli, when implementing automation and digitalization in manufacturing, manufacturers need to consider various regulatory aspects related to safety and security. He points out some key considerations under different heads like:
Safety Regulations: Machine safety, work environment, and electrical safety
Data Security and Privacy: Cybersecurity, data privacy, and IIoT security, and
Additional Considerations: Regular risk assessments, employee training, and regulatory updates.
“By addressing safety and security considerations and complying with relevant regulations, manufacturers can minimise risks, protect employees and data, and maintain compliance with legal requirements. It is important to continuously monitor regulatory changes and update processes accordingly to ensure ongoing compliance,” says Sureshnbabu.
When talking of digital transformation, there is always that issue of legacy equipment. How can the existing machinery and systems be integrated into a digitalized manufacturing environment, and what are the challenges in the integration process?
“Existing machinery and systems can be integrated into a digitalized manufacturing environment by leveraging open communication standards, such as OPC-UA and MQTT. OPC can be used, for example, to provide connectivity for software, such as HMI/SCADA to any existing PLCs and PACs, even if the controllers go back to the 1990s,” says Craig Resnick.
Amit Saluja feels this is the biggest challenge that comes in front of manufacturers looking to digitalize their plants, but also believes there are lots of innovative deep tech startups that have come up with workarounds to extract data from the machines by capturing signals. “In addition, there can also be options of placing sensors on the machines that provide a basic level of operations data like counts, vibrations, noise, working time, and electrical parameters. These approaches enable a good amount of operations visibility in the plant and help in condition monitoring of the critical assets,” he says.
Girish Ayya agrees: “Some components may require retrofitting, upgrading or replacing due to incompatibility with new technologies,” he says.
“Integrating existing machinery into a digitalized manufacturing environment can present challenges such as data silos, lack of standardization, technical expertise shortage, cybersecurity risks, high costs, downtime, data overload, change management resistance, and regulatory compliance complexity,” says Sureshbabu Chigurupalli. “To address these challenges, companies can collaborate with automation experts, invest in workforce training, and partner with technology providers. A phased approach, starting with pilot projects, can help manage risks and costs,” he concludes.
Note: The responses of various experts featured in this story are their personal views and not necessarily of the companies or organizations they represent. The full interviews are hosted online at https://www.iedcommunications.com/interviews)