The impact of AI and machine learning technology in revolutionizing manufacturing practices

In an interaction with Asia Business Outlook, BN Shukla, Operations Director, Jabil, India, shares his views on the challenges of interpreting and understanding the decision-making processes, strategies to optimize the implementation of AI & MI, robust measures to protect sensitive production data, how manufacturers ensure compliance with industry standards and regulations and more. BN Shukla, Operations Director for Jabil in India, has a career spanning more than 28 years with a specialisation in operational excellence and business management.

Considering the complexity of AI and machine learning algorithms, especially within critical manufacturing processes, how can manufacturers navigate the challenge of interpreting and understanding the decision-making processes of these systems?

Some of the common challenges in increasing the adoption of digital technology in manufacturing include: 

Capital investment: Varying degrees of costs — from IoT sensors used on existing machines, to purchasing large machinery with integrated machine learning solutions, to enterprise-wide infrastructure adaptations, particularly in large-scale projects. 

Effective change management: AI/ML are changing the way we do things as we merge the physical and digital together. Strategies must be accompanied by a support structure for employees, empowering them with the right tools and skills, thus creating a culture ripe for a successful transition. 

Technical skill gaps: Fuelled by digitalisation, the roles and expectations of the workforce — on and off the shop floor — are evolving. Talents that have “digital dexterity” and are ready to adapt and innovate in manufacturing processes and adopt digital tools that support those processes will successfully implement new technology and maintain operations. 

Data growth, sensitivity, and security: The physical and digital systems in smart factories make real-time interoperability possible. While large volumes of data are generated, challenges remain in data quality and management for decision-making, looming concerns over data and IP privacy, ownership, governance, and an increased risk of an expanded attack surface as numerous machines and devices are connected to networks.

To ensure the quality and reliability of the data used to train and optimize these systems, we have put in place several guard rails:

Datafication: We progress from digitization to digitalization to datafication, where we investigate business processes and transform the process into quantifiable data to track, monitor, and analyze. To do this effectively, we have set up an enterprise-wide Data & AI council, which involves senior members from all the functions to help identify key processes critical to the business and have the process owners work on critical data definitions, data lineage, and data sources. Although this is not technology specific, it helps to set a good foundation for the organization moving forward. Teams across Jabil are learning how to use data effectively to enable “Data to speak, data to act.”

AI/ML: Collected data that is not used effectively is a waste of resources. We leverage AI/ML/deep learning to extract value out of the swarm of data we collect each day from our factories and work processes to help deliver business insights, automate tasks, and advance system capabilities. Our AI/ML strategy spans from using AI algorithms to improve our inspection process in the factories. By using advanced data analytics to derive algorithms or new business models, we can gain new insights and intelligence for our business. We’re also developing our knowledge database and combining it with Generative AI technology to merge the insights from our self-healing manufacturing line (ready in April 2024) with the know-how of our workforce to continuously train our AI models and guide our technicians to take actions.

SAP S4: When Jabil migrated from SAP ECC to SAP S4 Hana in January 2022, we were able to offload the technical debt that came from 20-plus years of over-customization and subsystems that were peripheral to the legacy SAP system. The Hana database also brought about greater speed in data processing and a simplified data structure. Nevertheless, the benefits of SAP S4 migration should not be just about solving technical issues but about bringing new value for the users through new ways of report creation, enhanced user experience, increased productivity, and ability to leverage new functionality to transform the processes. We are still on the continuous improvement process to better leverage these functionalities and are bringing the users along in the transformation journey.

Automation: Process automation through the use of robotic process automation (RPA) tools has helped us automate many back-end office and repetitive tasks in various functions. Many functional teams who are using the RPA bots also try to “humanise” the bots and treat them as part of the (digital) workforce, measuring performance of these bots to ensure we obtain the maximum ROI. 

To navigate the challenge of interpreting the complexity in the decision-making process, it is crucial that organizations first have a clear strategy of how they plan to leverage AI/ML in the company. At Jabil, we took a customer-first approach, and we were deliberate from the onset. How we leverage AI/ML is about solving a business problem or providing deep insights to realize a step change improvement in safety, quality, delivery, and cost.  

Interpreting and understanding such systems, communications, and engagement with stakeholders are critical to ensure we are working on what matters to the business most.

In light of the challenge of ensuring scalability and adaptability across diverse manufacturing operations, what strategies can manufacturers employ to optimise the implementation of AI and machine learning solutions?

Once we knew what our “North Star” looked like, we were able to clearly break down obstacles within the People, Process, and Systems categories and develop solutions to take us to the next level. Some of these were:

Focus on people at the heart of transformations by taking an employee-first digitalisation approach. Many people are familiar with the saying, “AI will not replace people, but the people who can use it will.” With that in mind, the human factor is a major lever for transitioning and tapping into opportunities that come with AI/ML.

Our industry-certified internal courses, in partnership with industry experts and local universities, has allowed us to grow our pool of subject matter experts by ensuring that technological know-how is retained and expanded through customised application-based upskilling. Additionally, as engineers and technicians take business-related modules, they promote diversity in the workplace in the form of business differentiation and innovative decision-making.

Enhance industry ecosystem through public-private initiatives: In many of our locations, we partner with leading equipment providers and government agencies to build a strong manufacturing ecosystem. We must continue to actively partner with academia in creating the next generation of talents.

Amidst concerns regarding workforce reskilling and upskilling, how can manufacturers effectively foster collaboration between human workers and intelligent machines in manufacturing processes?

There are seismic shifts with the convergence of technologies across operations, information technology (IT), and supply chain, creating a data-driven environment that enables us to deliver the future of Jabil’s manufacturing. 

We need to embrace a work environment that is expected to blend advanced technology and digital skills with uniquely human skills, to yield the highest level of productivity. The rise of advanced technology can replace the manual or repetitive tasks many jobs entail. This frees up space for skills that are uniquely and essentially human, or so-called “soft skills,” including critical thinking, people management, creativity, and effective communication. Companies need workers that can exhibit these skills as well as digital skills to work alongside robots and technologies.

The broader aim of digital transformation is not just to eliminate tasks and cut costs, but to create value, safer workplaces, and meaningful work for people. Industry leaders need to put humans in the loop when preparing their workforce, through rethinking work structure, retraining and reskilling talents, and structuring the organisation to leverage technology and transform its business. 

There’s no one-size-fits-all answer to this, other than saying that digitalisation, digital transformations, and digital readiness of one’s operations and workforce is imperative to remain relevant and competitive in the long term.

We believe that the best way to make our organisation more data-centric and digital is to invest in those who are adaptable, curious, and flexible. We look to our existing and future talents with the logic that digital transformation is changing everyone’s role, from the factory floor to our executives. 

This marriage of multi-generational talents not only propels the industry forward, but it also heralds change within the industry itself, making manufacturing a destination for innovative jobs and being the continued change maker in India’s socio-economic landscape.

Given the cybersecurity risks associated with the adoption of AI and machine learning technologies in manufacturing, how can manufacturers implement robust measures to protect sensitive production data and mitigate potential cyber threats and data breaches?

At Jabil, we take cybersecurity seriously. Through our industry expertise and enterprise education and awareness efforts, we are building a data protection culture at Jabil, where our employees are empowered, and our customers and partners are confident in our ability to conduct business safely in today’s evolving digital world. 

Jabil delivers a three-pronged risk management methodology as part of our Defense-in-Depth approach:

Identify, protect, and block cyber threats;

Enable rapid detection of and response to cyber incidents;

Minimise and recover enterprise downtime in the event of an incident.

This layered system provides several levels of protection for data, not relying on any single tool or policy, and enables redundancy in our systems and processes.  

We manage digital security guided by the National Institute of Standards and Technology (NIST) Cybersecurity Framework (CSF), coupled with best-of-class solutions for data protection, threat detection and continuous monitoring within Jabil’s Security Operations Center (SOC).

Backed by policies and procedures to ensure enterprise resiliency, we provide robust and holistic risk-based guidance and high-quality shared cybersecurity services and solutions. In assuring that our capabilities are always relevant and updated, we use a leading third-party assessor to rate our security program as a whole and conduct penetration tests (PenTests) to monitor compliance with policy and identify gaps for remediation.

We have also built an effective security program that centers around technical controls and empowering our people to be our best line of defense by equipping them with top-tier cybersecurity education and awareness programs that provide them with the information they need to stay safe online in their personal and professional lives.

A great example is educating our employees before they click and providing best practices and tools to analyse site URLs after an individual click. We ensure our readiness to act if cyberattacks breach our defenses through continuous improvement programs such as tabletop exercises, a ransomware playbook, and incident response.