Sangram Kadam is the Associate Vice President and Head – Integrated Enterprise Solutions and Manufacturing IBU (India and South Asia) at KPIT Technologies
Interconnected smart machines have already transformed the shop floor in myriad ways. Machine-to-machine (M2M) integration enabled by the Internet of Things (IoT) has become a critical factor in capturing and extrapolating clean data to optimise productivity and streamline processes within factories. According to recent industry projections, there will be 3.3 billion M2M global connections by 2021. This makes it abundantly clear that businesses are increasingly relying on this new communications technology to resolve issues without the intervention of humans.
Does this mean machines are making humans obsolete? Not by a long shot.
Ironically, the human touch has been further enhanced by the advent of digital transformation because without humans, how will Industry 4.0 thrive? But it doesn’t just stop at this. The fourth Industrial Revolution, or Industry 4.0, has spawned yet another formidable manufacturing force: machine-as-a-service (MaaS). As per industry reports, machine learning as a service market is expected to exceed more than $3,754 million by 2022 at a compound annual growth rate (CAGR) of 42 percent in the given forecast period.
Machine-as-a-service has visibly shaken up traditional business processes. Manufacturers are now compelled to rethink their strategy and shift to a more service-based business model that aims to create better services and products. Thus, with the merging of manufacturing and services as one sector, the cyber physical systems, IoT, Industrial Internet of Things (IIoT) and cloud computing, connect not only machines with each other, but also enable humans to communicate with them in real time.
We’re at a point where machines have started providing services to different business functions. For example, consider the legal department that has historically been far removed from big data. Today, machine intelligence is disrupting even the legal scene by leveraging artificial intelligence (AI)-led platforms to crunch valuable data and eliminate time-consuming documentation work. Besides, analytics also reveal machines’ compliance capabilities in the context of industry standards and geopolitical realities. Even though it is a non-shop floor function, critical legal compliances such as product safety, data protection, adherence to health and environment standards, and export laws, among others, are aspects global manufacturers should be keenly aware of when they operate in different countries and jurisdictions. In my view, this forms the crux of business benefits accruing from MaaS. And remarkably, this has nothing to do with the core shop floor.
The nuts and bolts of machine-as-a-service
As the machine to human interaction (MHI) is rapidly gaining relevance, the industry’s perception and definition of machines has upended the status quo. Once considered purely a physical asset and a part of inventory, machines are now viewed as a business asset that effectively contribute to business goals. Clearly, the interaction of machines with business is a critical aspect of the industry’s transition to MaaS.
Moreover, the definition of machines has broadened, and it goes beyond the usual shop floor functions. As a result, machine-as-a-service doesn’t just contribute to inventory optimisation or production performance—it offers real-time data across departments and keeps a check on the ROI.
Leveraging the power of digital technology, MaaS has powerful ramifications for manufacturers. For one, machines can be purchased as a subscription model—as-a-service—without having to pay the entire amount upfront. For instance, all major automobile manufacturers have hopped onto this bandwagon and offer their customers subscription packages. This includes personalised services such as car servicing, insurance, roadside assistance, choice of accessories, and even concierge delivery, among other benefits. Even medtech manufacturers offer device-as-a-service to their customers for products such as MRI and ultrasound machines. These algorithm-driven systems collate and compare valuable data for their patients in a cost-effective manner. The payoff? A happy and satisfied customer who will give you repeat business. In this way, MaaS helps organisations remain competitive and move towards a business outcome that opens doors to new sources of revenue. This also reflects how the rules of machine ownership have changed to accommodate changing customer attitudes.
Another disruptor in today’s MaaS scenario is the changing nature of traditional machine lifecycle management. Earlier, engine oil was changed only after a vehicle clocked in a certain number of kilometres or a shop floor technician was called only when a machine broke down. But IoT has proved to be a game changer. It seamlessly streams data from machines, optimising maintenance tasks in real time and predicting system failures proactively. This is possible only due to embedded sensors and remote monitoring diagnostics that are solution-oriented technologies, heavily applied on today’s shop floors. Manufacturing units will shut shop if they fail to strategise the maintenance of assets by leveraging such cognitive technologies.
Also, as the service imperative becomes a key differentiator, machines will not only communicate with other machines but also support the C-suite in working towards an organisation’s larger business goals. Today, manufacturers recognise the need to develop customer touch points, starting from the purchase and installation of equipment to frequent software updates aimed at improving the bottom line performance and ROI. If shop floor managers can predict the breakdown of systems, a company’s business continuity would be higher, driving customer satisfaction.
Adapting to a smart factory environment is not as simple as it appears. Besides outdated infrastructure and shop floors, the global manufacturing industry also contends with standardisation issues, talent shortages, supply-chain complexities and fragmented customer demand due to increased competition.
Resistance to change from the factory workforce is something I have observed at close quarters, especially in the Indian context. The issues are manifold. Since the average age of the workforce is around 40, they fear adopting new technologies. But their bigger fear is potential job loss due to these tumultuous technological changes. The problem is further augmented when managers don’t extend support to the factory operators during this difficult transition phase or don’t involve them in the change process. Based on my own experiences, I am convinced change management is the biggest challenge for MaaS. Undoubtedly, better coordination between floor workers, the managers and the C-suite decision-makers is called for if MaaS has to prepare workers for a digitised future. In this context, human resources will play a critical role in reskilling and cross-skilling workers, as human capital is the most valuable asset for any organisation.
On the up side, there are also instances of true leaders turning the implementation phase to their advantage. For example, when a leading turbine manufacturer designed a computer numerical control (CNC) system, the management involved the machine operators in the initial discussions to understand how the new sequence of tasks would make work easier for them.
A culture of change should be cultivated through constant innovations that add more value to machine-as-a-service model. However, the test of true innovation lies in spending a million dollars in solving a billion-dollar problem. In other words, innovation should go hand-in-hand with business growth and customer satisfaction, and integrate the entire manufacturing ecosystem.
The road ahead
In my view, the journey to machine-as-a-service has already kick-started on a robust note. However, if manufacturing has to consistently undergo ‘new’ transformation, a strong implementation strategy is required to harness the wave of technological trends impacting the industry. Manufacturers should be willing to invest in disruptive technologies, try new approaches to manufacturing processes and be aggressive about applying innovative ideas through streamlined structures. Only then can we say machine-as-a-service will lead us to the next wave of industrial revolution.