Data analytics can help manufacturers investigate historical trends
Published on : Friday 01-07-2022
Titash Bhattacharya, Digital Transformation Expert.
For so many Indian companies who are not fully into Industrial Revolution 3.0, is there any urgency to move towards digitalisation?
Digitalisation is not only about becoming digital but understanding the purpose – what business problem is to be solved, the value we are generating and are we getting any competitor edge. Companies without being fully into Industry 3.0 still had a competitive edge. But with digitalisation or implementation of Industry 4.0 successfully, the solutions deliver irresistible returns. Digital transformation is revolutionising all aspects of manufacturing, touching not just processes and productivity but also people. The right applications of technology can lead to more empowered decision making. The companies are generating value in the entire manufacturing chain by increasing production capacity and reducing material losses, improving customer service and reducing their environmental impact. There have been significant reductions in machine downtime, improvements in productivity, and approximately 80% more accurate forecasting. These gains can fundamentally transform a company’s competitive position, e.g., one of India’s largest steel manufacturers, an organisation situated near the border, implemented an integrated security system. This system helped them to have insight into the number of people inside the plant at any given point. Now, during pandemic with additional sensors they were able to track social distancing, location based pattern analysis, man-down sensing, etc. With such data, companies are getting huge insights and are able to enhance their safety and security. With these benefits, companies are in urgency to move towards digitalisation.
The pandemic is nearly behind us, but the effects on industry will last longer. What are three digitalisation strategies that companies are working on based on lessons of the last two years?
Digital transformation isn’t a new imperative for business, but the pandemic has dramatically changed business models and forced companies to accelerate their digital initiatives, rapidly moving pilot programs into production. With the pandemic the digitalisation which would have taken years was completed within months. It can be clearly seen that the ‘Platform firms’ are dominating markets even more. Companies like Amazon, Big Basket, cloud kitchen companies, etc., are getting even bigger and stronger as traditional stores or business models are unable to compete. Therefore, companies will invest more in their ability to conduct business over the internet to be more resilient to potential risk like that of the pandemic.
Setting up COE: Many companies, by pursuing digital transformations as a theoretical exercise, are setting up independent delivery teams that are decoupled from business leaders, site operations, manufacturing excellence, and central IT. These COE centres are named as Digital Hub, Digital COE, Digital Lab, etc.
Building skills: Companies are looking to enhance their agility, speed and data-driven decision making while working on new opportunities for upskilling, reskilling, and cross-functional collaboration. They are working on a model for better talent attraction and retention and improved workplace safety and employee satisfaction.
Rebundling and customising: Many companies are using digital technology to rebundle their products or services to better serve their customers. This attempt will make it easier for customers to access their products or services.
Cost efficiency: Most of the companies are using digital technologies to improve their cost efficiency, typically through automation like robotics. This strategy is mainly aimed for getting a comparative advantage.
For many companies, the challenge is in moving from pilots to deployment at scale. What is the way forward?
Productivity, process and people improvements are not easy to accomplish at one shot, especially across a network of individual manufacturing sites, each with its own leadership, IT infrastructure, and workplace culture. It is not uncommon to hear of companies achieving impressive results through pilot programs at one factory site only to find themselves unable to replicate these local wins across their network.
a. Rather than performing a full and deep up-front analysis of an entire network, companies instead may focus on robust, accurate-enough insights that can be gleaned from individual units. Rather than having one-size-fits-all strategy, strategy for individual units should be framed.
b. To reduce the gap between the company’s vision, internal resistance to change and failing to set clear project objectives, companies should focus on developing a proper communication plan which will communicate well and often. Establish an effective engagement plan and regular communication with critical senior stakeholders, leaders and a cross-functional core team. This plan should include specific goals, with a 1, 3 and 5 years’ roadmap and should have buy-in from management and key stakeholders.
There is so much work going on in the area of Data Analytics. What about the effort to get real-time data directly from machines?
Embedded sensors and interconnected machinery produce a significant amount of big data for manufacturing companies. Data analytics can help manufacturers investigate historical trends, identify patterns and make better decisions. Smart factories can also use data from other parts of the organisation and their extended ecosystem of suppliers and distributors to create deeper insights. By looking at data from human resources, sales or warehousing, manufacturers can make production decisions based on sales margins and personnel. A complete digital representation of operations can be created as a ‘digital twin’.
With proper IT-OT integration the smart factory’s network can collect real-time data from sensors, devices and machines on the factory floor that can be consumed and used immediately by other factory assets, as well as shared across other components in the enterprise software stack, including enterprise resource planning (ERP) and other business management software. Cloud computing will be of great help considering the amount of data to be processed.
Is it too early to talk about standards and regulatory guidelines for collection, storage and access to data?
Standards and guidelines are required to establish technical specifications that are adhered to, and adopted by a wide range of manufacturers. The overarching goal is to increase reliability, predictability, inter-compatibility, consistency, and efficiency. Industry standards ensure that different products are compatible with each other and that customers can mix and match products from different vendors. They spearhead innovation, reduce costs, and enable a plethora of cost-effective and holistic solutions.
By employing standardisation in manufacturing and logistics, processes and procedures become more consistent and predictable, resulting in higher degrees of quality and efficiency. Total cost of ownership is reduced due to greater flexibility in terms of vendor and hardware compatibility and infrastructure setups. Additionally, implementing a well-established standard into existing platforms and solutions reduces engineering and development efforts in the long term due to familiarity working with the standard and the large community of users and contributors to the standard.
Several standards and associations have emerged with the shared goal of promoting interoperability, accessibility, and process automation in Industry 4.0. All of them satisfy a certain niche of the industrial production process, such as designing a digital twin of a product or production site, utilising sensors to optimise efficiencies, and various communication and software elements.
Digital transformation is deemed to be necessary for companies to become part of the big global supply chains. Are there already such requirements by big buyers as a condition to become their suppliers?
Industrial operations are dependent on a transparent, efficient supply chain, which must be integrated with production operations as part of a robust Industry 4.0 strategy. This transforms the way manufacturers’ source their raw materials and deliver their finished products. By sharing some production data with suppliers, manufacturers can better schedule deliveries. If, for example, an assembly line is experiencing a disruption, deliveries can be rerouted or delayed in order to reduce wasted time or cost. Additionally, by studying weather, transportation partner and retailer data, companies can use predictive shipping to send finished goods at just the right time to meet consumer demand. Blockchain is emerging as a key technology to enable transparency in supply chains. So, even without a formal condition a supplier may be out of business in case they are not in the technology league.
How could Digital Transformation help companies to cope with the supply constraints of recent origin – for example electronic chips, for example other shortages arising out of political events in Europe?
Surely the shortage of electronic chips is giving challenges for the companies but this requires holistic approaches to manage the supply chain. Companies must build in sufficient flexibility to protect against future disruptions. They should also consider developing a robust framework that includes a responsive and resilient risk management operations capability.
That capability should be technology-led, leveraging platforms that support applied analytics, artificial intelligence and machine learning. It should also ensure end-to-end transparency across the supply chain. In the long-term, risk response will need to become an integral part of business-as-usual protocols.
Titash Bhattacharya is a Digital Transformation Expert and possesses experience of working on 45+ large-scale projects both as consultant as well as Implementer in the field of Industrial Automation for sugar plants, refineries, chemicals, fertilizers, Power plants, Steel plants and Pharmaceuticals. He has also worked on multiple emerging technology initiatives like IoT, AI/ML, RPA across Smart Cities, Industrial Physical Security, and traffic management. This includes end-to-end engagement life cycle starting from business development, solution conceptualisation, cost estimation, solution architecture, defining technical specifications, preparing RFP/bid management to project management for solution implementation.
(The views expressed in interviews are personal, not necessarily of the organisations represented)