By Sarah Benhamou
When people think of manufacturing plants, most people imagine long assembly lines powered by futuristic robots, where everything is automated. In reality, though, up to 70% of factory tasks are still handled by humans, which means more than 70% of the tasks remains invisible to analytics.
Drishti, an Industry 4.0 pioneer and one of our portfolio companies, tackles this challenge by observing manual assembly lines and converting human activities into data, at scale. Drishti deploys cameras on live manufacturing assembly stations that use video traceability, remote visibility and AI algorithms to analyze human movements in assembling a widget or performing a task in order to identify workflow best practices and/or abnormalities. By lifting the curtain on these activities, and externalizing human tasks into measurable data, Drishti introduces an entire new subset of analysis to the manufacturing floor.
Companies like Drishti, known as Industry 4.0 solutions, are closing the loop between the physical and digital worlds:
– First, by capturing a constant stream of data from the physical world to create a digital record,
-Then, by analyzing and visualizing this data in order to enable connected systems to learn; and
-Finally, by applying algorithms to translate decisions and actions from the digital world back into the physical world.
The Industry 4.0 revolution has roots that trace back at least 30 years, to the intersection of breakthrough technological advancements in various fields (IoT, cybersecurity, 3D printing, big data analytics, AI, etc). However, we are only at the nascent stages of this movement. According to PwC, only 20% of manufacturers have implemented the “smart factory” at scale. Several key challenges present obstacles to broad adoption:
1.The Skill Gap — By and large, the manufacturing industry remains low-tech. Factory workers and plant managers lack the IT capabilities to implement smart solutions. According to a Capgemini survey, “more than 50% of manufacturer’s respondents find the deployment and integration of digital platforms and technologies a major challenge to scale up smart factory initiatives.” As a result, many manufacturing businesses fail to invest in technology solutions. And amongst those that do, experiments in introducing more advanced tools often fail not because they generate poor output, but because the workforce either lacks the understanding to process the insights or lacks confidence in the integrity of the results.
2.Risk Aversion — Another reason why manufacturers hesitate to adopt Industry 4.0 solutions is because the risk of failure is so high. Technical problems can cause expensive production outages, and the impact on output raises intolerable fears. This highlights the need for non-invasive solutions that are completely integrated with existing workflows, and that present a low-barrier to entry.
3.Business-Model Aversion – In an industry with such heavy CapEx requirements around new machines, material, equipment, etc, SaaS solutions present a paradigm-shift that challenges the dominant thinking. Rather than making a sizable, and measurable, investment into new materials, a SaaS solution forces the economic buyer to fundamentally shift their decision-making calculus and investment behavior, oftentimes in exchange for vague and unknowable ROI improvements.
4.The Data Optimization Challenge – The proliferation of sensors on factory production floors has armed plant managers with the ability to collect massive amounts of new data. Unfortunately, this data collection comes from disparate, and often, unrelated sources. A challenge, therefore, emerges in integrating data structures that are completely unconnected, and lack a common protocol, or language, with which to communicate. Under the circumstances, relevant decision-making remains obscure and poses an additional barrier for broad adoption.
5.Cybersecurity Threats — Undergirding all of the above points lies the cyber security risk. The more sensors you disperse, the more connected you are, and yet the more vulnerable you are to data breaches and/or hacks. What’s more, by connecting disparate systems together, you actually increase vulnerability to a single data breach. While this is an area of growing concern, many manufacturers in the industry today still have only limited visibility over their own cybersecurity threats. According to the CapGemini survey cited above, “fewer than 50% of organizations have the adequate data availability and cybersecurity measures in place, while nearly a quarter of manufacturers have experienced a cyber-attack in the last year.”
Despite the challenges, we, at BGV, are bullish on the future of the Industry 4.0 solutions, and strongly believe that the COVID-19 will accelerate the adoption of advanced technologies in the manufacturing sector. According to Silicon Valley Bank 41% of manufacturing executives are investing in accelerating automation due to COVID-19.
Recently, we have seen tremendous activity in this space, especially amongst startups focused on improving quality, enhancing safety, minimizing waste and ameliorating underperforming assets. Given the main challenges to adoption mentioned above, an ideal Industry 4.0 solution should fulfill the following criteria:
-Generate AI-enabled analytics that deliver actionable insights without the need for data scientists;
-Provide a low friction deployment model which does not require any process changes;
-Offer end-to-end solutions including services to address skill gaps and drive adoption;
-Include automated OT cyber security that absolves the need for a cybersecurity expert for proper implementation.
As innovative startups step up to seize upon this opportunity, those that can develop Industry 4.0 solutions along these lines are well positioned to capture a slice of this growing market. We, at BGV, are eager to partner with entrepreneurs that share this vision, and we look forward to making a small contribution to this evolution in the manufacturing space.
