Sundeep Sanghavi, Co- Founder and CEO,
With mobility, IoT, and analytics, having already become a reality in most factories, the challenge has shifted from figuring out what’s happening on the floor to what to do with all the information. Conventional computing machines are struggling under the load of petabytes of data - data that’s ideally supposed to provide you with insights to reduce machine downtime, increase productivity, and streamline overall operations. So what we need is the power to sift through millions of machine and sensor readings and shed light on machine behavior in a matter of minutes. Now, that’s a tall order for any human mind, no matter how sharp it is.
This wave of cognitive manufacturing that’s sweeping across the manufacturing industry smartens up the entire manufacturing process. It merges IoT, analytics, and advanced communication technologies to create “intelligent machines” that are capable of not only self-detecting and avoiding issues to reduce downtime and optimize performance, but also communicate with other machines to smoothen the entire manufacturing life cycle. In essence, cognitive manufacturing is the process of automating the process of big data analytics to facilitate optimized processes and thus, higher cost savings.
The truth is, the advantages offered by previous productivity enhancement techniques - lean production, outsourcing to low-cost countries, et al. - have long been exhausted. On the other hand, competitive pressures have only increased. Therefore, the focus now is on value creation to survive and differentiate from the competition. The disruptive technologies of a cognitive approach do just that - to begin with, they help you break the 20:80 pattern of asset failure, according to which merely 20% of all asset breakdowns are caused by predictable issues, and the rest (80%) are caused by random issues. A cognitive approach helps reduce such “random” downtime by up to 45%, while simultaneously increasing output by as much as 25%! All by merely leveraging data and analytics. At a time when manufacturers are facing relentlessly escalating margin pressures, this is the only way one can cope.
Industry 4.0 helps you smartly farm and leverage your data to unearth its true value - whether it’s in the form of insight-driven operational decisions, the adoption of predictive maintenance to avoid millions of dollars’ worth of machine downtime or the elimination of process inefficiencies. It builds a continuous and complete data flow, a digital string that runs through and binds the entire manufacturing life cycle, eliminating every little inefficiency along the way. The string begins building with product design and runs right through to recycling, where reusable parts are identified for further processing. The whole process is data-driven; therefore, at each step, data can be accessed, controlled, and communicated easily - something that thus far was impossible to do. Thus, industry 4.0 truly harnesses the power of the information formed by IoT.
Industry 4.0 is set to not just transform production the way we know it, but also the way we do business. The level of disruption that it entails across the value chain of production gives rise to several new opportunities that leverage the new value offerings available at each stage.
In particular, four distinct new business models are already emerging, leveraging the opportunities that it presents to collect, analyze, and share information. First, we have platforms, which offer a way to exchange products, services, and information. These can be further divided into interaction platforms, which function as “marketplaces” that connect and coordinate interactions between stakeholders, and technology platforms, which offer the technological infrastructure to develop advanced products and applications. The next business model is the “as-a-service” model, where automation service providers, instead of selling machinery, let buyers pay by usage - i.e., the buyer converts an initial, high CAPEX into a variable OPEX. The supplier also can drive higher revenue through subscription-based models. The third type of business model is IPR-based. This offers suppliers the opportunity to generate recurring revenue by leveraging proprietary data. Revenue, in this case, could be driven by offering subscriptions, training, consultancy services, etc. This model, possibly best leverages the power of knowledge in the age of information. The final type of business model is the data-driven model, which monetizes new ways of collecting and leveraging data.
If you’ve noticed, these new models depict a shift in profit streams - from physical product-driven revenue to data-driven revenue Thus, Industry 4.0 not only creates additional value, but also re-channelizes profit streams.
In an environment that is undergoing such extensive changes, agility is key to survival. Currently, most technological advancements are being driven by niche companies that specialize in very specific fields and are therefore more agile than large, well-established companies. Cognitive techniques to industry 4.0 gives you that much-needed agility. It automates your entire production ecosystem and provides you with critical updates, thus freeing you up to effectively address the challenges of rising resource costs, growing customization requirements, shorter lead times, rapidly changing customer requirements, and dwindling order sizes with the help of powerful, data-driven insights.
1.Evaluate your current assets to analyze which of them are underutilized and to identify potential new business models.
2. Set up control points to ensure sustained profit generation and avoid wasting effort and resources in areas along the value chain that have become more commoditized.
3. Stay updated and agile to adapt to changing market conditions and possibly capture the first-mover advantage by using cognitive approaches to predictive maintenance.
It’s obvious that successful implementation of Industry 4.0 depends heavily on the success of a company’s digital transformation. The planning, production, and business models - all revolve around a digital core, and cannot be managed with a partial digital transformation. Therefore, companies need to be prepared to shift to cognitive approaches to realize the true potential of Industry 4.0 - which goes beyond the mere elimination of process inefficiencies and in fact gives them the freedom to drive smarter decision-making and reinvent themselves in response to dynamic market shifts.
Remember - fortune favors the bold, but first, it favors the informed!