Six Trends Shaping the Digital-Savvy Manufacturer of the Future

The last 24 months have been rife with challenges not just for manufacturers, but organizations of all kinds. Those acute pain points, mostly brought on by the COVID-19 pandemic, intensified as the pandemic continued to wreak havoc and a breakdown in global supply chains led to extreme volatility.

Manufacturers are now looking to reduce their risk as it relates to an unrelenting supply chain crisis -- creating better controls over their own processes, while investing in automation, data science and technology to meet the ever-increasing demands of their customers.

Manufacturers will need better — ideally complete — visibility of operations and supply chains from suppliers and partners to the broader supply chain ecosystem. They'll also need to discover and develop efficiencies with an eye towards sustainability.

All of this drives the need to securely connect the plant and supply chain in the name of leveraging accurate and reliable data to make informed decisions. Or put more succinctly, to drive digital transformation.

With decades worth of experience helping large manufacturing organizations transform with innovative technology solutions, we've noticed a set of trends in customer challenges and outlook. Here are some of top trends we are seeing in the industry today.

Supply chain agility: Overcoming disruption through visibility and meeting customer expectations

Cracks in the supply chain that have been developing for years are now clearly exposed. Geopolitical forces, financial volatility and COVID-related workforce shortages in production, transportation, logistics and importation oversight have significantly increased costs and the time required to acquire raw materials, produce finished goods and deliver those goods to end customers.

Manufacturers need to collect and analyze data from internal and external logistical operations, using artificial intelligence (AI) and IoT to drive advanced analytics that can identify — or even predict — upcoming bottlenecks.

Manufacturers will also start to "nearshore" or "onshore" their operations, bringing them closer to both suppliers and consumers. This improves access to materials and parts, and reduces the complexities, dependencies and time required to get products in the hands of customers. It also reduces the need to build excess inventory to weather supply chain disruptions.

Sustainability: Now an obligation, not a tick in the box

Consumers are demanding action from both governments and companies to combat climate change in meaningful ways. Improving efficiencies and reducing waste in the manufacturing process while meeting stringent emissions targets are all emerging as internal priorities for manufacturers, with data and visibility of operations being key to driving improvements.

Facility design considerations, process improvements and supply chain strategies such as onshoring and localized suppliers will play a big role in meeting the net-zero greenhouse gas economy targets.

The Re-Rise of Edge: Complementing the cloud

For years, manufacturers have struggled with the notion of a "cloud first" strategy. While many view cloud as the way of the future, the path to cloud transformation is challenging. Determining which systems, applications and data are cloud appropriate versus what should remain localized requires an in-depth understanding of not only cloud architectures and solutions, but the complexities, dependencies and operational requirements of manufacturing.

Certainly, cloudified architectures are critical to digital transformation efforts. However, integral to any cloud strategy, edge computing bridges the gap between non-real-time cloud solutions and the production systems that require real-time processing, analysis and visualization of data.

Plant floor operations that require real-time data and decision making are leveraging data at the premise edge to automate otherwise manual processes saving time, money and resources. And edge is becoming increasingly relevant to manufacturers' ability to facilitate rapid AI solutions and improve operations.

Low-hanging use cases for edge computing on the factory floor include:

• Moving storage or mission-critical resources out of centralized data centers and closer to the sources of data (i.e. the edge) to leverage smaller compute modules with built-in AI capabilities (AI-on-chip).
• Modernizing the core operating environments such as HMI, SCADA and Historian components to leverage technologies such as containerization.
• Enabling cloud deployments of MES and ERP, providing localized resilience and accelerated processing.

Digital: Thread, twins and more to predict outcomes and assist operations

The concept of digital twins and threads has been accelerated in recent years due to the increasingly pervasive nature IoT and use of sensors, technologies which are now maturing and more affordable.

The concept of digital twins can be leveraged not only as a virtual representation of a particular product or part, but also to replicate manufacturing and distribution processes and systems, which allows companies to make changes to staffing or procedures by testing them virtually prior to being rolled out physically.

Major fulfillment centers across the globe have leveraged this type of technology (prior to and after COVID-19) to reduce exposure to their staff and improve people and product placement efficiencies.

The Emergence of AI: Taking the leap from pilot to production

AI in manufacturing environments is transitioning from being a novel technology confined to discrete pilots or proof of concepts to mainstream environments.

AI leverages data being collected across the plant and equipment (enabled by the IIoT) and applies modern computational power to mimic the problem-solving and decision-making capabilities of the human mind. AI-based solutioning and engineering is being applied to solve physical problems in manufacturing processes across entire operations and product lifecycles.

Leveraging AI models, the systems can be trained to both monitor, adjust and analyze the process – preventing downtime, improving efficiencies, and preventing the supply chain challenges mentioned earlier. This improves agility, reduces risk, shortens time-to-market and increases profitability.

As AI is applied to more processes, manufacturers will see compounding gains from significantly improved accuracy, speed and insights in the manufacturing process.

Security: Strengthening to avoid disruption

Digital transformation requires the convergence of industrial automation, information technology and data science. Now more than ever manufacturers must ensure that they have robust protections and procedures in place to deal with security related events.

Security breaches can be severely disruptive to local operations, even putting human safety and the wider supply chain at risk.

Asset and process visibility tooling provides a real-time understanding and baseline of normal operations, while threat detection, prevention and remediation solutions inspect and protect the access and communications in and around production environments. 

Comprehensive end-to-end security across both the IT and OT environments within a plant will protect the business and enable the confidence to maximize the benefits of digital transformation.

Conclusion

As manufacturers continue their Industry 4.0 journeys, data stands as their biggest and best strategic weapon to accelerate digital transformation and combat unforeseen challenges, such as a pandemic or pinched supply chain. However, manufacturers often struggle with the development and execution of a digital transformation strategy that aligns data science and technology with defined business outcomes, encompasses legacy production systems, and ensures the protection and integrity of the operation.

A wave of next-generation applications and services made possible by an array of critical, maturing technologies — such as cloud, edge and AI, among others — will go a long way to producing the real-time, actionable insights that drive business and operational improvements while reducing risks.

Embracing the ideas and trends listed above will help. If you need help with any of these, our unique understanding of the manufacturing landscape, paired with an unparalleled expertise in data science and technology, can help take you to the next level with:

• Digital Transformation strategy
• Alignment of data science and technology to business goals.
• Accelerated decision-making insights in manufacturing and distribution operations
• Modernized workforce and customer experiences.

Please visit our Manufacturing industry page or email us at manufacturing@wwt.com to discuss your Digital Transformation plans.