A radical shift in consumer behavior accelerated by the COVID-19 pandemic has exponentially expanded the wide-scale adoption of e-commerce and online purchasing. As consumers increasingly make online purchases for standard items like groceries and household supplies, this shift is likely to become permanent ― creating a significant impact on warehouse operations and creating new opportunities for innovation.

Early winners so far in this business environment have been the technology-embracing early adopters such as Amazon and Ocado, who have innovated with robotics and software to create more efficient, durable supply chains. However, there’s room in this space for all players who are prepared to adopt warehouse automation and robotics. It’s likely that those who don’t participate in this disruptive innovation risk being left behind.

Adapting to Warehouse Challenges

Traditionally, robotics has been applied in repeatable, fixtured applications such as those on automotive assembly lines. Now, artificial intelligence (AI) and the Internet of Things (IoT) are enabling breakthroughs in robotic perception and complex decision-making in real time. This allows robotic technologies to operate effectively in more complicated, unstructured environments such as the warehouse and distribution networks.

Due to the inherent modularity and scalability of robotics systems for picking, sorting, and palletizing, organizations of all sizes can reap the benefits of these innovations while making warehouse operations more efficient, cost-effective and safe. The ability to add solutions with a high return ROI, intermixed with manual processes, make them ideal candidates for investment in existing manual facilities.

The Robotics Opportunity

The rise of e-commerce has stressed existing parcel and distribution networks to their limits. Faced with a huge need for the efficiencies and increased capacity that warehouse automation can fill, a new breed of intelligent robotics solutions has started to go mainstream. The scalability of these solutions makes them a good fit for an industry that is still mostly manual, and they are a logical next step. For many enterprises, warehouse automation adoption is lagging significantly or absent altogether. According to DHL research, 80% of warehouses remain manually operated. Another recent survey indicates that the greatest investments to date are in conveyance (63%), while robotic palletizing and picking are still very low (15% and 8%, respectively).

Major e-commerce companies know that nimble, automated supply chains are key to meeting demand and staying ahead of the competition. To keep up with these major players, smaller and emerging e-commerce companies must take the right steps to automate their warehouse supply chains too.

Every Season is Peak Season

Prior to the pandemic, e-commerce and logistics were geared toward the peak season (early November through January). Distribution networks would ramp up for peak, then struggle with underutilized capacity for the remaining nine months. In 2020, the peak began in mid-March and hasn’t slowed. The challenge now for many smaller enterprises is how to innovate and grow within a peak environment that never subsides. Enterprises no longer have the luxury of a downtime during which to upgrade facilities to increase capacity and integrate new technology.

The e-commerce giants have an easier time integrating new technology organically because their technology stacks are already built. Smaller enterprises must work to bridge this chasm. One of the advantages of advanced robotics is that it can be integrated into operations without taking down a system or facility. Robotics can be added little by little, in a modular fashion, without major disruptions.

The Holistic Approach

There is now a significant need among both types of businesses to explore the best ways to develop, productize, and scale solutions across their entire distribution networks. By adopting a customized holistic solution that addresses key challenges and provides insights across their IT and warehousing infrastructures, companies now have an opportunity to drive continuous improvements and create flexible, robust supply chains that can keep up with increasing customer demands.

“We are here to put our shoulders to the wheel of progress,” MLC Co-founder David R. Brousell told the hundreds of live and virtual attendees in his opening remarks at the MLC’s new Manufacturing in 2030 event, which opened in New Orleans earlier today.

“We can’t be certain about what tomorrow will bring, let alone what might be in 2030,” he continued. However, “we can project or extrapolate based on current trends and conditions, with a reasonable amount of probability, what the shape of manufacturing will look like in 10 years’ time.”

Well before the pandemic, noted Brousell, manufacturing companies were altering their organizational structures, in part due to the influence of technologies that were increasingly empowering more people with information, shifting from hierarchical, command-and-control models to flatter, more collaborative ways of organizing people and processes. As a result, manufacturing is now harnessing its intellectual capital much more effectively than ever before.

“All around us, conventional notions of what can be accomplished in production as we understand the potential of new technologies, how we arrange work and processes based on new organizational forms, and how we leverage the creativity of our people, are being reimagined,” he said.

There will continue to be challenges ahead, of course, from continued global disruptions, to redefining the relationship between humans and machines, to the increasing urgency of combatting climate change and how to create more sustainable, digitally enabled, circular business models. “Competitive advantage will flow to the companies that master these challenges,” he added.

But there will also be massive opportunities too. In the decade ahead and beyond, Brousell believes that factories and plants will be distinguished by a now evolving set of technological, organizational, and leadership characteristics that will set them apart from facilities of the past. “The extent and depth of change ahead of us will be profound”, he predicted.

That’s why events such as Manufacturing in 2030, and the MLC’s upcoming year long M2030 Project during 2022, is so vitally important to help manufacturers explore, understand, and plan for, the shape of things to come for the manufacturing industry over the next decade.

“If we do things right in the next 10 years,” stressed Brousell, “we have the opportunity to create the greatest engine of manufacturing production humankind has ever seen.”

Aircraft manufacturing demands the highest-quality materials, highly trained experts, rigorous quality control, and precision processes that remain largely manual. These demands make it an ideal candidate for a digital reinvention.

By combining major leaps in operating technology (OT) with integrated IT for a fully optimized environment, aircraft manufacturers can take advantage of recent advances in automation and analytics to improve manufacturing speed and accuracy and reduce waste, making manufacturing cells both more efficient and sustainable.

Challenges abound

A single-aisle commercial aircraft contains tens of thousands of nutplates. The manual installation of each one takes three to four minutes.

This process is repeated thousands of times over the life of the craft as plates are removed and reinstalled for routine maintenance. Until now, nutplate installation has been done manually, exposing manufacturers to risks including:

• Human error: Over the course of tens of thousands of manual actions, mistakes are inevitable. The potential for error is compounded by the small size of nutplate components, which make them difficult to handle and increase the potential for mistakes.
• Rising costs: Beyond the sheer labor cost of time on the job, the associated errors of manual installation lead to increased costs through scrapped materials, poor inventory management and time-intensive quality control.
• Inefficiency: Manual installation often requires down time for changing tools and changing shifts. It also limits visibility across the manufacturing environment, which means that resources are sometimes unavailable or poorly optimized.

To meet today’s demands to become more sustainable and socially accountable, manufacturers must also find ways to reduce the waste and inefficiencies inherent in their legacy processes, and the aerospace industry is no exception.

Tremendous Potential

To address these multiple challenges, automated manufacturing and robotics technology provider, JR Automation, has deployed Hitachi Vantara’s Lumada Manufacturing Insights in its  SmartAttach™ manufacturing cell as a way to merge the huge advances in automation at the operational level with superior insights at the informational level to help drive a comprehensive shift toward smarter aerospace manufacturing for the future.

Semiconductor Market Trends

The semiconductor industry has been growing at a rapid pace for the past few years. Market research firm IDC estimates that  the semiconductor industry grew at a rate of 10.8% in 2020 and will grow at 12.5% this year, resulting in a $522 billion market sector. IDC attributes much of this growth to the impact of COVID-19.

The increased demand for semiconductor chips is due to new generations of smartphones, tabs, laptops, and desktop computers used in industries such as healthcare for telehealth services; in the education sector for online teaching and instruction; and as more people worked remotely. At the same time, the automotive industry, a heavy user of semiconductors,  is packing more and more chips into vehicles as it attempts to offer all the creature comforts  consumers want as they embrace the connected car experience.

In the manufacturing sector, too, the pandemic has driven home the values and virtues of setting up connected factories that enable contactless manufacturing and uninterrupted operations in the face of a crisis. All these trends indicate  that the demand  for semiconductor chips will rise steadily in the  future. Despite the rosy growth projections, the semiconductor industry still faces challenges, chief among which is continuing to innovate even as it delivers expected price/performance improvements.

Therefore, it is imperative that the industry invest more in research and development to drive innovation while at the same time optimizing costs by leveraging technology such as cloud computing.

If one examines the key attributes and requirements of the semiconductor industry – skilled resources, high competition, complex automation tools, data and IP, differences in industry supply chains, and the brief shelf-life of  designed chips,  it is apparent that these factors are highly expensive and difficult to manage. Given the level of  investments and expertise required, there are very few players in this industry. The race for excellence is fierce, and a considerable effort and investment is dedicated to driving R&D to identify areas and avenues for innovation.

Faster time to market through the acceleration of design cycles, performance enhancements of chips through upgrades and updates, and IP protection through foolproof and flawless security systems are the top three business priorities of this industry. The chip companies invest most of their time, energy, and capital in fulfilling these priorities. However, operational priorities are equally important, such as driving efficiencies in the manufacturing process through data analytics; optimizing  operations, processes, and costs; and driving productivity through collaboration.

Cloud computing provides a reliable and seamless infrastructure to address both the business and operational priorities of the semiconductor industry.

Reasons to Embrace Cloud

1. Faster Time to Market and Quicker Design and Development

The ever-increasing demand from consumers for products with higher compute powers and processing abilities has resulted in shorter product lifecycles, requiring semiconductor manufacturing companies to bring products to market faster.

To this end, applying cloud computing in the semiconductor industry offers scalable storage, big data analytics capabilities, and enhanced productivity with collaboration tools for reviews and feedback that enable quick product launches.

Cloud also provides a flexible, scalable, elastic, and secure infrastructure for chip designing by providing on-demand compute for EDA tools. It enables semiconductor manufacturers to set up and access high-performance computing (HPC) power with virtual machines (VM) images, enabling quicker design and development cycles.

2. Improvement in Foundry Operations and Yield

Cloud offers a data lake or repository that enables storing, processing, analyzing, and inferring the foundry’s generated data. Manufacturers can use data insights for predictive performance and analytics as well as the management of resources in their supply chains, thereby improving  production uptime and yield. It also allows for specific artificial intelligence and machine leaning use cases for fault detection in the production line using imaging techniques and smart analytics tools.

3. Smarter Manufacturing Powered by Democratization of Data and  Analytics

Chip designs evolve with each release, and the chip design companies have families of chips in incremental progression/evolution cycles. The chip lifecycle data must be logged, analyzed, and processed for value generation. Cloud Service Providers (CSPs) like Amazon Web Services offer storage and analytics capabilities to chip design companies to apply AI and ML models for systematic data processing. They also provide the necessary infrastructure to integrate IoT and implement Industry 4.0 solutions for smart and connected manufacturing .

4. Improved Collaboration, Transparency, and User Productivity

The semiconductor manufacturing industry is highly competitive, and the success or failure of a chip manufacturer entirely depends on the ability of the manufacturer to collaborate effectively with an  eco-system that includes suppliers, OEMs, and internal teams for design reviews, feedback, and testing.  Cloud infrastructure provides a centralized system to track the productivity of the different stakeholders, enabling transparency and boosting efficiency, especially in the current times of COVID 19 using collaboration tools such as MS Teams, Google Workspace, and Google Meet.

5. High Operational Efficiency  

Unlike on-premise data centers managed by internal IT teams with constraints on skill, availability, and resources,  cloud infrastructure is managed by specialists such as GCP, AWS, and Microsoft. These service providers have made huge investments in R&D, infrastructure, and resources, and provide service-level agreements which ensure uninterrupted operations for semiconductor foundries.

6. Higher Service Levels Due to Better Availability

One of the primary reasons for the semiconductor industry to not adopt or scale cloud has been the business criticality of its operations. However,  modern-day CSPs provide SLAs that comply with industry requirements and, in some cases,  go beyond to ensure reliability. For example, GCP provides a robust architecture with high-bandwidth connectivity across 25 regions and 76 availability zones to deliver global services.

7. Organizational Agility and Flexibility to Scale-up 

The use cases for sensors, chips, computing, IoT, and Industry 4.0 are ever-increasing. It is thus imperative for the semiconductor industry to be extremely agile and offer unmatched on-demand scalability and flexibility to ramp up/down its compute infrastructure to accommodate R&D, design, testing, and validation of GTM activities. Analytical capabilities to draw insights and make quick decisions must also be in place in order for the industry  to deliver on its reputation of being agile. Cloud offers all these capabilities to the industry and at the same time drives home the cost benefits, security, and efficiency.

8. Backbone for Driving Innovation

There are several aspects of cloud infrastructure that can drive innovation for the semiconductor industry. To begin with, it can provide a leeway for the industry to squeeze in cost efficiency to a perceived rigid cost structure. The possibilities of leveraging IoT, AI,  ML, big data analytics for gaining visibility, and driving efficiencies throughout the chip manufacturing value chain are tremendous. It can provide EDA support, high-performance design, HPC, and High Volume Manufacturing (HVM) capabilities that will enable  better outcomes at lower costs.

9. Cost Efficiencies

Cloud offers instant scale and capabilities to perform and execute operations across the semiconductor value chain from design to yield without investing in physical on-premise data centers, reducing infrastructure development costs. It provides a collaborative infrastructure for value chain stakeholders to review and test the designs and offer feedback irrespective of the location of the stakeholders. Chip manufacturers can also drive the cost efficiencies on account of improved uptime owing to predictive maintenance capabilities and the security that cloud infrastructure offers.

10. More Secure Environment for IP Protection

The semiconductor industry powers a host of other industries, and several of these industries manage data categorized as highly sensitive, IP, business-critical, or compliance-driven. The dedicated investments by the CSPs in ensuring the security of their cloud infrastructure is an added advantage for the semiconductor industry to ensure data and IP protection for its clients. These CSPs provide more secure and reliable infrastructure at lower costs than the on-premise setup. For example, Google’s global-scale infrastructure protects billions of users with world-class security.

In Conclusion

The semiconductor industry has been a pioneer in enabling digitalization across industries. With Industry 4.0 and IoT gaining prominence, the use-cases of semiconductor chips have evolved rapidly from device-specific applications to sensorization, integration, and communication areas.

However, the irony of this industry is that despite being the transformation catalyst for all the other sectors to adopt digitalization, the industry on its own has been lagging when it comes to the adoption of technologies such as cloud computing for cost optimization, innovation, and streamlining operations. According to KPMG, even when most other technology industries have been adopting digital transformation at a rapid pace of 89%, the adoption rate of the semiconductor industry remains at a paltry 50%.

Considering the outlook for the semiconductor industry, utilizing the cloud for digital transformation is the only way the  industry can scale and position itself to meet  consumer demands for speed, accountability, security, innovation, and reliability.

Intertape Polymer Group (IPG) is undergoing a digital transformation, and it’s doing it without an army of data scientists and data engineers, revealed IPG’s Vice President of Business Transformation, Jai Sundararaman, during the MLC’s 2021 Rethink Summit this week. Instead, the company is rolling out its digital analytics platform by doubling down on process engineers and its operational excellence team.

When IPG, a producer of packaging and protective solutions with 27 manufacturing plants around the globe, began its digital transformation journey about three years ago, it quickly became apparent that, despite a plethora of articles on the topic of M4.0, there is no proven industry playbook companies can take off the shelf and implement, noted Sundararaman. “Success is hard-earned and based on experimentation,” he added.

The first thing the company did was to make a capital investment in its digital transformation, based on broad-based support from its operations leader, CEO, CFO, and board, “Which is critical,” stressed Sundararaman. IPG investigated more than 15 analytics platforms, with help and input from data from the MLC as well as advice from other MLC members. While no one platform is going to work for everyone, he noted that the MLC network had helped IPG shape its thought processes in these initial stages and determine which platforms to take on a pilot run.

The next investment was in talent. “It’s about rescaling and upskilling the talent, as well as establishing what we call the Digital Process Center of Excellence,” he added. “Our mantra is, ‘We believe in empowering employees with technology’…people are going to learn and grow as part of the process.” This means that the company didn’t double down on analytics per se. “We doubled down on our continuous improvement and process engineering. My team are the subject matter experts on the process side, and they work along with IT and OT specialists and the Continuous Improvement team, all of whom have a dotted line relationship with the plant teams. So when they go into a plant, the process is streamlined. This enabled us to get commitment for the resources as we scale across the plant.”

While IPG is still in the early phases of scaling analytics around multiple plants and executing pilot programs, it is already seeing success. “We have noticed the ROI is less than two years, which we’re very proud of,” said Sundararaman. Its work in centralizing management systems has also proven to deliver successful ROI. Still in the early phases are projects around augmented reality, virtual reality, and 3-D printing, though those also look promising.

One key to success thus far has been how IPG is leveraging analytics through process excellence. “It starts with a mindset, and commitment, and cultural enablers,” he said. “It’s not going to happen in one shot.”

Because success is not guaranteed, you must also be willing and able to embrace failure along the way, he advised, and learn from those failures to move forward. Don’t be too quick to come to a standardization mindset either, he noted. The technology continues to evolve, so the journey will be ongoing.

“The most prudent thing is to focus on what will create business value,” emphasized Sundararaman. “The value is critical. It’s not Step 5. It’s Step 1 through 5. We have been very meticulous in terms of our approach to where value creation will be, how we engage the different partners, and how to capture that value as we go on through the process.”

And you have to be willing to take risks, he added. There are tools, methodologies, and some pointers and guideposts along the way, “but you have to figure it out and then take a leap of faith.”

“We are in the midst of great change,” declared David R. Brousell, Co-Founder, Vice President, and Executive Director of the Manufacturing Leadership Council (MLC) in his opening speech at the MLC’s 2021 Virtual Rethink Summit today.

“It requires us all to reimagine the art of the possible – to expand our visions, to adapt, to devise new strategies, and to orchestrate change,” he said. “How well you transition to the digital model of doing business will be key to the competitive posture of your company and, as a result, our industry as a whole.”

Reflecting on the massive global disruption of the past year, Brousell noted that the COVID-19 pandemic’s impact on manufacturing has not only been profound but, in many areas of activity, has also led to permanent changes.

“Who could have imagined that as a direct result of a worldwide pandemic, Manufacturing 4.0 would suddenly arrive at an inflection point in its history,” he added. “Spurred by the crisis and the consequent need for greater flexibility and agility, manufacturing companies began accelerating their investments in digital technologies and the changes necessary to fully exploit them.”

Brousell cited the latest MLC survey research which confirms that 54.8% of manufacturing companies believe COVID-19 has increased management’s focus on digital transformation. Powerful majorities also report that many of the COVID-driven changes will now become permanent elements of their leadership approach. For example, 68.2% say that new disaster preparedness plans, resiliency strategies, and response teams will become permanent features in their companies. Likewise, 57.3% say that more collaborative, cross-functional organizational structures will take root. And 62.2% expect remote working by both leadership teams and employees to continue to be part of everyday life.

“More and more,” he predicted, “the digital model of doing business will sweep through other functions of the manufacturing enterprise – sales, marketing, HR, service. With manufacturing operations leading the way, the rest of the manufacturing enterprise will digitize.”

“So, open your minds over the next three days of Rethink and imagine a better future for manufacturing,” Brousell advised the hundreds of Rethink Summit virtual attendees. “Now is the time to think big about manufacturing.”

Schneider Electric’s Lexington, KY, plant is one of only a handful of manufacturing facilities in the U.S. that enjoys the coveted status of being a World Economic Forum-designated “Lighthouse” factory. To achieve that distinction, the Lexington plant, built in 1957, had to address some very basic operational issues.

In a presentation yesterday at Rethink, the Manufacturing Leadership Council Summit conference, Kenneth Labhart, North America Innovation Leader at Schneider, said that one of the issues that had to be addressed was the plant’s inability to share data from the plant floor that could be used to improve operational performance.

By adopting M4.0 technologies and approaches, including IoT, cloud, mobility, and analytics, the Lexington team focused on transforming the facility’s connectivity and integration platforms to break down silos and allow its teams to share data more easily. Those transformation projects have already resulted in a 26% reduction in energy spend, mean-time-to-repair reductions of 20%, the elimination of paper processes, and a five percent reduction in downtime.

The initiative was part of a smart factory program that began in 2017. Today, 80 Schneider factories have deployed a digital transformation roadmap.

But Labhart was clear that the company’s digital transformation had its challenges, chief among which were employee pushback, executive leadership buy-in, and expertise in digital technologies.

Schneider was able to overcome these challenges using a careful approach. “It is very important to take small steps,” Labhart said.

What draws the next generation of leaders to a career in manufacturing?

While the specifics may vary from person to person, it’s the challenge, and the satisfaction, of seeing a product through from design to being in the hands of satisfied customers in the best, fastest way possible while continuously learning all along the way, according to members of the Next-Generation Panel session at the MLC’s 2021 Rethink Summit this week.

The three 2021 Manufacturing Leadership Award Winners on the panel — Kat Duggan, Coatings Business Learning Leader at Dow; Kasia Karimee Garcia Bracho, Supply Chain Lead at IBM; and Katia Valenzuela, Communications and Design Association, MxD — had so much enthusiasm for their chosen career path that the audience at the virtual event couldn’t help but cheer them on.

Duggan said her experience so far has “really been a joy,” while Valenzuela added, “It’s such a wonderful, innovative world…it was like [I discovered] a treasure trove of opportunities I didn’t even know existed within manufacturing.”

To thrive in that continuously innovating world as it moves into the future, next generation leaders will need some hard and soft skills that perhaps their predecessors did not, such as how to quickly analyze data to make critical decisions, let go of past traditions, and have the flexibility to be open to new ideas, new tools, new technologies, and the new M4.0 culture. Future leaders, they said, must be open and empathetic, able to listen and contribute back to their communities, and able to collaborate with all the people on their teams.

To attract the next generation of leaders, manufacturers also need to ensure that their workforce, especially at the upper echelons, are diverse. As Valenzuela said, “It’s very important to see people who look and act and think like you do in positions of leadership, not just because they bring their own diverse set of perspectives, experiences, and knowledge, but also because they can give someone like me a role model to look up to.”

Bracho also emphasized the importance of fostering a culture where everyone feels welcomed and respected. “Let’s be active and proactive” when it comes to hiring from the outside and promoting from within, added Duggan.

Sustainability is also important to the next generation, they added. New technologies such as blockchain can increase transparency and trust in a company’s ability to maintain standards at every stage of manufacturing. While local or global regulation may drive some sustainability efforts, consistent consumer pressure is ultimately what’s going to change business attitudes and how money is spent.

Bracho cited an IBM survey of more than 414,000 people in nine countries that found environmental responsibility to be a key factor for consumers. “The trend toward sustainability is growing, and it’s something that companies should focus on,” she said.

As to what we’ve learned from the pandemic? Digital is going to be the biggest winner for manufacturing, they said. And with that increasing focus on digital technology comes adaptability, flexibility, a culture of continuous improvement, and the need for an increased focus on cybersecurity.

Manufacturers are generating more data, faster, and from more aspects of their operations than ever before. The key to harnessing all that data to produce higher quality products more quickly and efficiently, and to speed up the decision-making process, is having an intelligent platform and good data governance strategies, agreed Sid Verma, General Manager of the Manufacturing/IIoT Division at Hitachi Vantara, and Mike Lashbrook, Vice President of the Esys Division and Digital Solutions at robotics automation company, JR Automation, during an Executive Dialogue at the MLC’s Rethink 2021 Summit this week.

An M4.0-ready intelligent platform should have several key components, they said. It must enable operators to understand the data being generated and present it in a form that enables users to create analytics or decision models. It must also be able to provide intelligent output based on those models.

To make the system work enterprise-wide, it must also be able to talk to both the OT and enterprise sides, said Verma. And it must be scalable, fault-tolerant so it can self-correct, and the user interface must be consistent with the way people naturally work and think. It  should also be flexible and easy to maintain.

This all sounds good, but how does it work for manufacturers who are still in the process of automating their legacy systems? The increasing need to improve data quality across all the key performance indicators is driving the push toward intelligent platforms, said Lashbrook. “We have an enormous amount of data and intelligence being collected from connected equipment and smart sensors…the system needs to be able to ensure that, if there are small changes in the system, you can adapt on the fly and still get good quality.”

The future, he added, will be a completely integrated digital twin system that can quickly enable the operator to come up with the production model they need to move forward without disrupting the system.

There are challenges to scaling these platforms to where they need to be to achieve a full M4.0 operation, they acknowledged. “It’s a journey for us as a platform company to learn and adjust to be able to provide that value that the OT world needs,” said Verma. IT companies like Google make it look easy, because everything was IT-enabled and the protocols are clean. When you get to the OT side, however, it gets more complicated, depending on the age of the assets and the volume of data involved. While internet companies can just collect all that data and scale it, it gets too costly and difficult to follow their example on the plant floor.

The main challenge is the explosion of data being generated, which session moderator, MLC Co-Founder, Vice President, and Executive Director David R. Brousell called “the 400-pound gorilla in the room.” According to MLC survey data, manufacturers expect up to a 500% increase in data volumes over the next two years as they become more connected.

“Just collecting data on the OT side does not work for us” in the same way it works for a Google, said Verma. “We have seen horror stories where people spent their entire IT budget just collecting data because they didn’t know where to start.”

“Step one has to be stepping back and working with the operational focus. What are those KPIs whose operational efficiencies you want to improve? Then we have to make sure that we collect data around those, not just collect everything,” Lashbrook said. The approach is to focus on the value you’re hoping to create, then collect data associated with that value and figure out which aspects of the legacy systems need adjusting. “In the future, we can look at creating connected systems from day one. But for now, we have to work through these challenges.”

Verma agreed that companies should work upfront to develop a business priority, and a business use case that has an associated ROI, then bring in the engineering expertise. “If you are looking for predictive maintenance, let’s target the most critical failure that can happen. Then let’s try to collect the data to address just that particular failure mode. That way we limit the cost of the solution and the value goes back to the business.”

Many companies don’t have data scientists on staff to help analyze the data, but that shouldn’t stop them, said Verma and Lashbrook. “The first phase of deployment for industry 4.0 is to get that expert knowledge from people in quality and maintenance using older systems and automate that information,” said Verma.

For example, if a technician hears a noise when a motor fails, put in an acoustic sensor that can be alerted when the tech hears that noise. Once your models start showing more accuracy, then companies can begin to layer in data science on the areas that are most business-critical. “That has been our recipe for giving incremental value and industry 4.0 at a much lower cost profile,” he said.

Lashbrook added that, if you don’t have the expertise in house, bring in partners that can fill the gaps. For longer term solutions, look to hire people who have the new skillsets you will need.