Leading manufacturing enterprises confidently invest their organisational spend and time on engineering, training and implementing technology solutions to instigate machine-to-machine communication and IIoT networks. Does this integration facilitate the overall smart manufacturing ecosystem? How does IIoT play a critical role in advanced materials and manufacturing?
The manufacturing world is recently disrupted by many technologies and newer inventions like advanced composite materials, energetic materials, anti-biofouling coatings, magnets, superconductors, anti-hazard gadgets and more. With the manufacturing domain augmenting with time, the need for closely-connected fleets of smart machines has never been so important. From a technological perspective, manufacturers are now highly dependent on IIoT-driven smart machines- for a plethora of very good reasons. Today we will be educating the reader on how beneficial it is for a manufacturing centre to adopt a full-phased IIoT smart machine fleet and why.
The manufacturing world is recently disrupted by many technologies and newer inventions like advanced composite materials, energetic materials, anti-biofouling coatings, magnets, superconductors, anti-hazard gadgets and more. With the manufacturing domain augmenting with time, the need for closely-connected fleets of smart machines has never been so important. From a technological perspective, manufacturers are now highly dependent on IIoT-driven smart machines- for a plethora of very good reasons. Today we will be educating the reader on how beneficial it is for a manufacturing centre to adopt a full-phased IIoT smart machine fleet and why.
What Exactly is IIoT-driven Smart Machine Integration
Manufacturing practitioners of the new generation are mainly reliant on fleets of smart machines. Smart machines have allowed industrial systems to be wholly or partially dehumanised. The best way to make time-sensitive, critical and event-driven decisions is to utilise the best man-made resource of all time: data. This is where IIoT enters the world of manufacturing. IIoT, when expanded ‘Industrial Internet of Things’, is the industrial application of IoT encompassing the interrelation between all ‘things’- core systems, people, companies, stakeholders, machines, sensor networks, production processes, instruments, super technology suites, advanced materials and more. It basically allows the manufacturers to extract data flowing from disparate data sources accommodating the IT ecosystem of an organisation.
As manufacturers of the next generation are highly-dependent on data, they employ 100s to 1000s of smart machinery to automate their manufacturing operations. The concept of a ‘smart factory’ is revived with machine-to-machine integration of smart machines spurred by the power of IIoT. This technological disruption has led manufacturers to witness newly-found standards of predictability of operational events, flexibility and agility in production, plus means to cut down the negligible wastage of organisational time, money and effort.
As manufacturers of the next generation are highly-dependent on data, they employ 100s to 1000s of smart machinery to automate their manufacturing operations. The concept of a ‘smart factory’ is revived with machine-to-machine integration of smart machines spurred by the power of IIoT. This technological disruption has led manufacturers to witness newly-found standards of predictability of operational events, flexibility and agility in production, plus means to cut down the negligible wastage of organisational time, money and effort.
Benefits of IIoT-powered Smart Machines for Today’s Manufacturer
The convergence of industry 4.0 and IIoT technologies have broadly impacted (for good) manufacturing sectors paramountly. There are many manufacturing advantages that follow after the careful adoption of IIoT-based smart machine fleets in manufacturing establishments which are important to be noted by manufacturing giants of this era. Here are some of the main benefits of adopting IIoT-driven smart machine networks in your factories, warehouses and any other industrial vicinity.
Interconnectivity of Machines with Unequal Intelligent Functionalities Levels
IIoT-driven smart machines enable the robust accumulation of manufacturing big data ranging from slight actuating or sensing data to the full control and optimisation of end-to-end operations. The seamless data streams enabled by IIoT through our smart machine networks enables many modes of communication, including:
- Machine-to-objects communication,
- Machine-to-people communication,
- People-to-machine communication, and
- People-to-objects communication.
The data collected due to this interconnected mesh allows manufacturers to collect enough insight to strategise manufacturing functions like manufacturing, packaging, warehousing, logistics, and more, in the most optimal manner. This feature of IIoT-powered smart machine fleets contributed to the emergence and maturity of new technologies like pervasive sensing, big data analytics, cloud computing, edge computing, cyber security and more.
FUN FACT: Shockingly, even in the world’s largest manufacturing country -China- with 76% of their enterprises in the electronic and electrical appliances sector use sensors to collect data, but only 33% of them use big data technology to analyse the data gathered. Yet the rate of interconnection grows rapidly with time.
FUN FACT: Shockingly, even in the world’s largest manufacturing country -China- with 76% of their enterprises in the electronic and electrical appliances sector use sensors to collect data, but only 33% of them use big data technology to analyse the data gathered. Yet the rate of interconnection grows rapidly with time.
Complete Autonomous Operations (As A Part of An Even Larger System)
IIoT-driven smart machines fleets led to an abrupt increase in automation levels in the manufacturing world. The importance is that this automation happens as an integral part of an even broader interconnect system; in other words, IIoT allows the manufacturing systems to be autonomous in a scalable manner. The data extracted by IIoT-powered smart machines can be fed into optimally trained AI algorithms to:
- Automate enhanced multi-connectivity of new devices,
- Interconnect Autonomous Guided Vehicles, Unmanned Aerial Vehicle, Forklifts etc.,
- Automate iterative decision-making,
- Automatically digitise manufacturing environment via simulation,
- Enable wireless data entry,
- Enable SDA (Software Defined Automation),
- Power up mechanical components to ensure embedded safety of the smart machines automatically and more.
Thus, interconnecting the end-to-end ‘things’ of the IIoT system leads to the accumulation of invaluable data from a broad range of applications, devices and other data sources. The data collected due to this interconnected mesh allows manufacturers to collect enough insight to strategise manufacturing functions like manufacturing, packaging, warehousing, logistics, and more, in the most optimal manner. This feature of IIoT-powered smart machine fleets contributed to the emergence and maturity of new technologies like pervasive sensing, big data analytics, cloud computing, edge computing, cyber security and more.
Leverage Data for Better Manufacturing Insights
Connecting the dots between operations and other functional sectors of manufacturing establishments are phenomenal in making overall organisational decisions in a manufacturing firm. The unfaltering data streams flowing from smart machines can be fed to visualisation and analytics technologies to get clearer, border and reliable manufacturing insights. IIoT data generated by smart machine fleets can be coupled with simulation platforms, digital twins, AI and ML models, smart and intuitive dashboards, manufacture metrics models and more to gain insight.
For example, when the AI and ML schemas of the mechanisms behind the analytics technology tools are trained under realistic technologies, they can use the data of the smart machines to understand the OEE levels, performance integrity and efficiency of in-house machines compared to the near-real-time market demands. This decreases the memory costs astoundingly and allows unchallenged data management opportunities, accurate operational decisions and reduces backlogs for data-driven manufacturing specialists.
For example, when the AI and ML schemas of the mechanisms behind the analytics technology tools are trained under realistic technologies, they can use the data of the smart machines to understand the OEE levels, performance integrity and efficiency of in-house machines compared to the near-real-time market demands. This decreases the memory costs astoundingly and allows unchallenged data management opportunities, accurate operational decisions and reduces backlogs for data-driven manufacturing specialists.
Understand Smart Machine Competencies Transparently
Understanding the actual functionality, health and performance of the smart machines will help the manufacturers to dodge prolonged downtimes, huge economic threats and operational inefficiencies that can detrimentally impact the productivity of the organisation.
Having better insights into smart assets can also help manufacturers in minimising the overall total cost of ownership of non-financial assets of the production or warehouse facility. It improves the safety of the manufacturing assets and enables effective predictive and prescriptive maintenance approaches to ensure that manufacturing devices and machines are in their best state- both conditionally and structurally. Data extracted by early detection sensors and other asset security technologies can help manufacturing asset operators to keep smart assets under close supervision and ensure there is no unscheduled breakdown, threat or risk that can affect the productivity, operational excellence and competitive advantage of the manufacturer.
Having better insights into smart assets can also help manufacturers in minimising the overall total cost of ownership of non-financial assets of the production or warehouse facility. It improves the safety of the manufacturing assets and enables effective predictive and prescriptive maintenance approaches to ensure that manufacturing devices and machines are in their best state- both conditionally and structurally. Data extracted by early detection sensors and other asset security technologies can help manufacturing asset operators to keep smart assets under close supervision and ensure there is no unscheduled breakdown, threat or risk that can affect the productivity, operational excellence and competitive advantage of the manufacturer.
Cerexio Manufacturing Technology Powered by Smart IIoT Integration
Cerexio is one of the few competent technology solution enablers that offer new-age technology solutions for smart machine-oriented manufacturers of the new age. We offer optimal PLC and instrumentation services to help your manufacturing team get the best out of your organisational data with minimal effort. Moreover, Cerexio’s AGV Fleet Manager is a solution that helps you tailor an interface that allows you to control 1000+ AGV and UAV devices in one remote location. The data extracted from the elastic and reliable IIoT networks of your factory will be manipulated by this technology suite to empower smart dashboards, Digital Twins, Simulation Platforms, Asset Maintenance Models, Predictive analytics Tools, Asset Security Protocols, Event-driven Process Scheduling and many more options. Connect with Cerexio to inquire more about this exclusive IIoT-driven technology suite for optimal remote smart machine control.
Imperatives That IIoT-driven Smart Machine Integration Belongs to The Future than The Current
Informative research conducted by Accenture (NYSE: ACN) predicts that despite the economic crisis that the global economy is impending, IIoT could enormously contribute to the world’s output with USD 14.2T by 2030. They reminded that the potential economic benefits of IIoT depend on the careful adoption of digital technologies by manufacturers and risk mitigation strategies taken by the government to the economic and social wellbeing of their countries. The contribution of IIoT of smart machines in the manufacturing sector can burst open the growth of mature markets, open new ways for revenue flow avenues and facilitate innovative market trends in future.
An accompanying report posted by the Accenture Forum also statistically indicated 87% of the global business leaders perceive the IIoT technology and the interconnection of the smart machines will act as a net creator of employment opportunities to a new calibre of innovative and forward-thinking employees. People who are more tech-savvy will gain better opportunities in employment. For example, a manual packager will be able to upgrade to a job where the operator can operate the smart packaging machine remotely. This allows the operators to collaborate with other related professionals, like data analysts, engineers and peers, to ensure that the operations are timely, optimised and precise during packaging.
The advancement of IIoT-driven smart and integrated fleet systems in the manufacturing world allows domain experts to reimagine and witness the dawn of a new level of manufacturing excellence. With time, manufacturers will gain the opportunity of capitalising on data value to optimise service-based offerings and pay-per-use financial models that benefit organisations and clients mutually. Centralised control, prediction of impending machine failures, strategic calibration of manufacturing processes based on events and many more smart decisions are all achieved in a shared effort with this technological advancement. Therefore, manufacturers of today must fear to meet the future today.
The advancement of IIoT-driven smart and integrated fleet systems in the manufacturing world allows domain experts to reimagine and witness the dawn of a new level of manufacturing excellence. With time, manufacturers will gain the opportunity of capitalising on data value to optimise service-based offerings and pay-per-use financial models that benefit organisations and clients mutually. Centralised control, prediction of impending machine failures, strategic calibration of manufacturing processes based on events and many more smart decisions are all achieved in a shared effort with this technological advancement. Therefore, manufacturers of today must fear to meet the future today.
