First, some good news. Over the last couple of months, the manufacturing industry has witnessed the beginnings of recovery, although we are well aware that the industry has been badly hit and disrupted by the pandemic.

September PMI^TM data from IHS Markit indicated the sharpest improvement in operating conditions across the U.S. manufacturing sector since early-2019, shown in the figure below. Overall growth was supported by:

• A faster expansion in production and a solid rise in new orders
• As a result, firms continued to broaden their workforce numbers

As hiring increased following further upward pressure on capacity.

But manufacturing giants have absorbed the shocks and built strong responses toward business growth. They are steering away from the traditional notion of being on the shop floor, and moving toward remote monitoring production in real-time, data and cloud-based solutions to become agile.

In many ways, the pandemic has forced organizations to hit the brakes on daily operations, but in other ways, it has created an added emphasis on speeding up their technology adoption efforts. Organizations are now implementing digital solutions like artificial intelligence just to maintain their standard operations.

For the manufacturing industry, 2021 will be a period to recover, re-invent, and run. Sensors and the Internet of Things (IoT), real-time visibility into supply chains, cloud and analytics, automation and remote operations will inject agility, intelligence, and efficiency into the sector.

Take for instance Honeywell using data and tools to make business decisions faster, enable remote work, and ensure safety of workers. Or, Corning quickly gearing up to their commitment toward their customers in the bioprocessing space.

Though this is a great start, transformation is happening in pockets and most organizations are missing out on long-term success by not focusing on the right technologies. What will it take for manufacturers to sustain progress and move toward business growth?

In the modern world of manufacturing, the industry faces endless disruptions, supply chain visibility challenges, monitoring and maintaining health and safety of the workforce, and keeping productivity at optimum levels amidst constant battling of uncertainty and experiencing major impact on their business.

The COVID-19 crisis has severely challenged the resiliency and preparedness of manufacturing companies, with the situation calling for a multifaceted approach, actions, and future-proof transformational steps designed not just to preserve and protect business models but also help in assuring customers and communities of their continuity and commitment.

Redefining manufacturing operations with Artificial Intelligence and Machine Learning

The pandemic was a wakeup call for the manufacturing industry. Organizations realized that they needed a heightened ability to respond, change the way they think about health and safety, and take control of their costs. This has accelerated the adoption of Industry 4.0. In my previous article, I had covered ten potential digital manufacturing opportunities and the long-term approach to investments. Technologies like Artificial Intelligence and Machine Learning are proving to be key enablers that can change how manufacturing works and have some clear benefits.

• Using data as a strategic asset: Manufacturers will have to manage with half their workforce on shop floors and the rest working remotely. The adoption of AI and a range of collaboration tools, combined with remote monitoring, will help enhance the productivity onsite. Leveraging IIoT and 5G will increase connectivity and provide valuable data for visualization, and AI-based insights. The data available can be used in machine learning to enhance real-time monitoring. And real-time monitoring will help troubleshoot production delays, demand and supply management. For instance, Nokia leveraged Machine Learning to alert assembly line operators to any inconsistencies in real-time processes.
• Digitalization as a competitive advantage: AI and IoT can enable predictability and availability of systems and supply chain operations. Companies that have embraced these technologies early are already seeing a 7% revenue growth advantage over their peers, McKinsey found. Machine learning will help predict quality by combining various input parameters like raw materials, time to process, RPM etc., to delivery higher quality levels.
• Future-proof supply chains: As manufacturers look out for local, low-risk suppliers to supply critical parts to mitigate the demand disruption, digital tools and processes will help manage supply chain risk and accuracy leading to faster digitization of supply chains. ML can help improve planning across various functions like sales, account management, and finance leading to increased accuracy of demand forecasts. Danone used machine learning to increase their demand forecast accuracy by 30%.
• Driving new business models: By embedding connectivity in industrial equipment and products, manufacturers can increase revenue opportunities. By using smart technology, they can bring down product lifecycle costs for the end customer and accelerate new commercial arrangements such as SaaS recurring payment models. For instance, Wipro enabled 15% savings for a heavy equipment manufacturer with asset intelligence.

Technologies like Artificial Intelligence and Machine Learning will help manufacturers build robust processes and gain leading-edge capabilities to bounce back to business.

For example, in industrial manufacturing, it is critical to balance supply and demand in accordance with market dynamics. Disruptions such as those brought on by COVID can be minimized with multi-layer supply chain monitoring systems with heuristics applied for demand sensing, leading to effective management of disruptions. Applications such as Work.com by Salesforce are a step in the right direction for remote workforce management while industries open up.

Building AI/ML capabilities in organizations

If AI had the power to transform organizations, why don’t most organizations not have these technologies already?

Starting up with AI might present some challenges. It is important to consider whether your organization is ready and aligned to the vision:

• The leadership team should have a clear vision for AI initiatives
  
• Organizations need to implement and empower workforces for AI-enabled processes
• The present and future roles for AI need to be clearly defined
• Organizations must be prepared to see return on investments eight months to a year later
• Analytics and AI capabilities must be in line with business goals
• Organizations must have AI translators that require deep company and AI knowledge

The right team is essential to creating and maintaining AI systems. This kind of talent is difficult to find. Adoption can be accelerated by upskilling current employees or looking for the right partner who can bring in the most skilled data-savvy engineers, data specialists, AI creation experts and multi-skilled project managers.

Companies can also leverage an AI adoption framework like the one Wipro has built. The STRL framework – Sense, Think, Respond, and Learn, to help customers use AI across their value chain to identify patterns and make predictions and build insights and outcomes from the data.

The future of manufacturing with AI/ML

As organizations build their AI capability and leverage technologies like AI/ML to redefine their operations, they will grow toward sustainable business success. We believe that the future of manufacturing driven by AI/ML will pivot on the 4Rs.

1. Responsible: Manufacturers will be able to operate with a renewed focus on health and safety. They will be able to manage their shop floor productivity with greater operational efficiencies and real-time remote monitoring.
2. Resilient: Organizations will be resilient to any external stimuli. The pandemic is an example. But external stimuli could also mean a new product innovation by a competitor or a start-up. The agility and nimbleness of an organization to quickly re-boot and re-configure the entire value chain of concept to sell will define its success.
3. Reliable: The economic and social downturn caused by COVID-19 will create a much deeper divide between manufacturers who have just started to digitize and those who are much further ahead in their digital journey. Future-proof supply chains and robust operations will define a clear competitive advantage.
4. Responsive: Consumer patterns will change with low affordability after the lockdown. SaaS-based business models will help them respond to changing customer demands. Design thinking and digital technologies, such as artificial intelligence (AI), digital twins, and 3D modeling will also help organizations design for cost over and above usability and customer delight.

Organizations must leverage data and analytics to create new business models and operational excellence while ensuring security and quality. In order to achieve a stat of global supply chain, AI-ML driven systems play a critical role in helping organizations enhance decision-making while enabling process automation to secure innovation and scale programs to deliver tangible results.

Read more about fostering manufacturing growth amid the pandemic and beyond here: https://www.wipro.com/process-and-industrial-manufacturing/form/jumpstart-american-jobs-making-it-here/

Ashish Saxena

Vice President and Business Head, Manufacturing - North America, Wipro

Ashish has 25+ years of experience leading many Fortune 500 and Global 1000 client relationships across Asia, Europe, and North America.