Authors: Karthik Natarajan, Guru Mahesh
The Industrial Internet of Things (IIoT) leverages AI-powered automation, machine-to-machine communication, and real-time analytics to transform how manufacturers operate. It connects a network of industrial devices to build a collaborative manufacturing ecosystem with greater operational resilience to overcome complexities in the supply chain and meet market expectations, thus enabling smart maintenance.
With the reigning popularity of smart devices and advanced sensors in the manufacturing sector, organizations are now collecting and analyzing data for actionable insights, adding value across the workflow. These interventions have altered the approach to industrial maintenance, shifting it from reactive to proactive procedures, fueled by accelerated digitization.
Time dimension has gained prominence with solutions looking to address anomaly detection, failure prediction, reliability forecasting, and digital technical assistance in fieldwork with speed and accuracy. Beyond ensuring availability, performance, and efficiency, smart maintenance in a competitive market triggers a domino effect across operations, product, service, and customer dimensions with the aim to deliver greater customer satisfaction.
Evolution of the smart maintenance mindset
With the supply chain disruption it created, the pandemic has exposed rampant vulnerabilities of global logistics and production strategies. With competition in the industry peaking, organizations are expected to be exceedingly efficient, customer-centric, and resilient. For product teams, the advent of smart devices has guaranteed a steady stream of quality data and inputs from product implementation. Combined with Maintenance-as-a-Service, analyzing data can optimize energy consumption and predict asset wear-and-tear while highlighting service metrics, including warranty period, price, etc.
With the right framework, this could translate to gaining traction and ROI for any organization. Let’s look at how we at Tiger Analytics make this possible.
Tiger’s framework for optimized ROI on smart maintenance
The Tiger framework focuses on excellence in five key areas to deliver the best ROI on smart maintenance.
A single error in product functionality could translate into a disaster for manufacturing teams. Smart maintenance with remote monitoring is a gamechanger in this aspect. Adopting preventive and proactive maintenance will ensure efficiency along with saving valuable time that can fine-tune resolution. Using smart maintenance for functionality analysis will help identify product-feature fit with a focus on ease and feasibility of maintenance, safety, etc. Smart maintenance can help in optimizing the production and product, allowing the organization to compete on pricing in the larger market. Smart maintenance here also ensures real-time tracking of issues to avoid oversight of wear-and-tear that might trigger product failure or threaten workplace safety. Additionally, it schedules routine inspections as per criteria and recommends the replacement of assets. The sensors identifying this can also be equipped with the necessary configuration to send alerts in case of any conflict or alteration in the criteria, mitigating unplanned downtime and wastage.
Energy consumption analytics and optimization focus on energy management for deep-dive analytics and smart maintenance to address manual blind spots in the production process. Insights around energy consumption of equipment, warranty plans aligned to equipment usage along with visibility to the KPIs/metrics associated with services offered would enable manufacturers to deliver value to their customers. Smart maintenance enables energy consumption analytics, data-driven maintenance plans, and visibility to service metrics/KPIs.
Smart maintenance ensures optimal inventory by assessing usage patterns and data from proactive monitoring. Combined with the ability to analyze existing stock, it mitigates overstocking or understocking, which leads to a loss of revenue. Digital assistants, driven by NLP capabilities to understand organization-specific context and vocabulary, increase the support team’s responsiveness in real-time, allowing field technicians to work efficiently with quick and relevant suggestions. Going further from digitized user manuals, AR is now capable of remotely evaluating maintenance processes, cross-checking manuals, and conducting inspections with smart glasses or through handheld devices, accelerating the time to onboard new field technicians and provide them with in-depth information.
Remote Condition Monitoring
Remote condition monitoring with a cloud-hosted data delivery platform can gather and share insights about asset anomalies, predict system failures based on patterns, and make more accurate forecasts on the need for repairs. This reduces maintenance costs while increasing asset uptime and performance. Together with Edge devices that bridge several information gaps, these bring unprecedented levels of awareness to the maintenance ecosystem with data analytics capability to reduce the storage burden on network resources.
Smart maintenance helps you improve bottom-line revenue by better understanding customers’ usage of field operations, end-of-life services, or spare parts to provide data to determine value. This can help you grow your revenue by meeting their needs at the right time.
If you found this blog useful, check out our detailed whitepaper on Optimized ROI on Smart Maintenance of the Future on how we helped clients address these issues.Tags: AI in Manufacturing Smart maintenance