Edge Computing can be commonly referred to as a distributed computing frame that minimises the proximity between an application of a system solution (like data analytics tools or visualisation tools) and disparate data sources. The unruly growth of computing power after the emergence of industry 4.0-recognised technologies like AI, IIoT, Digital Twin, Simulation and impending technologies like the 5G capability makes automation and digitalisation a mandatory upgrade for all business systems. Therefore, new-age manufacturing is also demanding to utilise Edge Computing to prevent themselves from falling behind. Today, our informative blog archive will present this article to help the reader understand how Edge Computing can optimise manufacturing decisions, accelerate the growth of manufacturing efforts and result in seizing tangible advantages and benefits in their company.
Why is Edge Computing Important?
Edge Computing and many other data technologies have disrupted the industrial world, making every decision that an industrial practitioner makes be scaffolded by data-driven insights. Thus, Edge Computing was renowned by almost all industries for its ability to move data analytics tools closer to data sources like data lakes, mainframes, applications, cloud drives, IoT devices, data warehouses, data storages, local edge servers and more. This technology outshines data processes and analytics that take place in shared traditional data centres or cloud-driven platforms. Edge Computing is much faster and more accurate than its alternatives; therefore, it was recognised by every industrial domain.
Sending data back and forth to centralised analytical points or to a cloud-driven location requires time and results in latency in processed data. On the contrary, Edge Computing does not require data being transferred from one location to another; instead, it processes and analyses data within the closest proximity to where it was created in the first place. With Edge Computing, data does not have to traverse; therefore, it results in a very short latency rate and significantly faster data insights during operation. Therefore, the deeper and quicker insights generated by Edge Computing leads to better customer satisfaction, resourceful financial decisions, faster processes and lesser risks for all companies that exploit its features.
Sending data back and forth to centralised analytical points or to a cloud-driven location requires time and results in latency in processed data. On the contrary, Edge Computing does not require data being transferred from one location to another; instead, it processes and analyses data within the closest proximity to where it was created in the first place. With Edge Computing, data does not have to traverse; therefore, it results in a very short latency rate and significantly faster data insights during operation. Therefore, the deeper and quicker insights generated by Edge Computing leads to better customer satisfaction, resourceful financial decisions, faster processes and lesser risks for all companies that exploit its features.
Is Edge Computing Used in The Manufacturing Industry?
Edge Computing did not take a long time to be a buzzword in the Global Manufacturing Domain for its exquisite benefits in guiding companies to make faster, accurate and effective data-driven organisational decisions. Understanding the true impacts of Edge Computing for a manufacturing company can help forward-thinking companies to capitalise on organisation data and use new-age technology solutions to slim down decision making processes from a few months to a few minutes.
Manufacturing solutions like quantum, storage, power and mainframe systems that inherit features empowered by Edge Computing, AI and other out-of-the-box technologies are used to apply smart technologies at the edge. Most futuristic manufacturing players use Edge Computing to digitise their systems with AI, IoT and Big Data to move to the competitive edge without any disruptions. However, is it evident that manufacturing systems can house multiple solutions but fail to interconnect them using the right technology; even at instances like that, Edge Computing coupled with hybrid cloud services can benefit from centralising and accelerating data actions to fit manufacturing companies’ requirements profoundly. To dig deeper into how Edge Computing helps, let us look into a few advantages of Edge Computing for manufacturing companies.
Manufacturing solutions like quantum, storage, power and mainframe systems that inherit features empowered by Edge Computing, AI and other out-of-the-box technologies are used to apply smart technologies at the edge. Most futuristic manufacturing players use Edge Computing to digitise their systems with AI, IoT and Big Data to move to the competitive edge without any disruptions. However, is it evident that manufacturing systems can house multiple solutions but fail to interconnect them using the right technology; even at instances like that, Edge Computing coupled with hybrid cloud services can benefit from centralising and accelerating data actions to fit manufacturing companies’ requirements profoundly. To dig deeper into how Edge Computing helps, let us look into a few advantages of Edge Computing for manufacturing companies.
Advantages of Edge Computing for Manufacturing Companies
Understanding the advantages of Edge Computing can help manufacturing companies discover innovative ways to improve their companies on an industrial or enterprise scale. Starting from maximising the efficiency in executing operations, upheaving performances, reassuring the safety of manufacturing operations to automating core manufacturing processes are surely advantages that a manufacturing practitioner cannot miss. Edge Computing certainly contributes to all these benefits and more plus despite the changing demands and external impact on manufacturing processes, it will ensure the availability of resources, time, money, workforce and more in meeting desired goals and productivity levels. Here are some of the main benefits of Edge Computing that made this technology touted among most manufacturing firms for being an indispensable technology upgrade.
Accurate and Agile Asset Condition Monitoring
Edge Computing plays the main role in allowing manufacturing practitioners to keep track of the conditions of their expensive industrial assets. Getting faster access to asset data via IIoT networks overcomes all the drawbacks of asset maintenance efforts in age-based or routine-based asset management. Relying on data analytics to predict asset condition, risk trends, impending failures, and detecting criticality, reliability and serviceability levels of assets enabled tangible benefits for most manufacturing asset managers. They can ensure that manufacturing assets in their factory infrastructures, starting from a single nut or bolt to expansive conveyor belts, do not face prolonged downtime or spontaneous expensive failures.
Edge Computing can therefore be very optimal in saving a lot of time in inspecting and analysing asset conditions plus pre-emptive detection of future machine failures with laggard-free data manipulation. It allows faster insights to make investments in assets, reduce the risks of assets and ensure the best performance statuses of assets at all times. Especially in asset networks, if data is being processed close to the end-device, manufacturing companies would gain the luxury of saving their time, money and effort astoundingly. For example, if a pump shaft is deflated, the IIoT-driven sensor attached to it will trigger an alarm, and the edge computing features can use the data of the shaft to quickly prescribe the necessary maintenance protocols that the pump manager can follow to stop it from being detrimental for the performance of the whole mechanical system.
Edge Computing can therefore be very optimal in saving a lot of time in inspecting and analysing asset conditions plus pre-emptive detection of future machine failures with laggard-free data manipulation. It allows faster insights to make investments in assets, reduce the risks of assets and ensure the best performance statuses of assets at all times. Especially in asset networks, if data is being processed close to the end-device, manufacturing companies would gain the luxury of saving their time, money and effort astoundingly. For example, if a pump shaft is deflated, the IIoT-driven sensor attached to it will trigger an alarm, and the edge computing features can use the data of the shaft to quickly prescribe the necessary maintenance protocols that the pump manager can follow to stop it from being detrimental for the performance of the whole mechanical system.
Optimising Manufacturing Services
One of the most impactful challenges in the manufacturing sector is successfully leveraging multifaceted advantages that are rooted in highly standardised and automated manufacturing processes. Also, meeting the dynamic demands and personalised requirements of clients can be unique from one client to another. Making manufacturing services fluid enough to meet the user-defined requirements as a service can be equally challenging to most manufacturing service enablers.
Manufacturing-as-a-service can be fluid and mobile if the company allows all clients to use a shared platform to communicate their unique requirements. When clients use a shared portal to submit thousands of differentiating product requirements, your company must ensure that they are not frustrated by laggard services. The first step towards ensuring that your systems are flexible, you need to reassure that your manufacturing service is available 24/7 despite the geographical distance you have between your manufacturing facilities and the clients. Therefore meeting stringent latency requirements, which is driven by mission-critical operations in executing manufacturing processes, can be a heavy responsibility.
Data processing at the edge can, therefore, outperform centralised data analytics or cloud-driven data processes because it will securely manipulate data at the edge of the end device. Edge Computing enables amazing network, compute and storage capabilities for custom manufacturing service platforms and can even be extended to state-of-the-art shopping experiences for clients. For example, Edge Computing can facilitate clients in virtually visiting a digital twin shop floor via AR or VR technology and request unique product amendments based on their requirements and submit it to the core systems of the manufacturing company. Edge Computing can make online shopping experiences and communication so much faster and easier.
Manufacturing-as-a-service can be fluid and mobile if the company allows all clients to use a shared platform to communicate their unique requirements. When clients use a shared portal to submit thousands of differentiating product requirements, your company must ensure that they are not frustrated by laggard services. The first step towards ensuring that your systems are flexible, you need to reassure that your manufacturing service is available 24/7 despite the geographical distance you have between your manufacturing facilities and the clients. Therefore meeting stringent latency requirements, which is driven by mission-critical operations in executing manufacturing processes, can be a heavy responsibility.
Data processing at the edge can, therefore, outperform centralised data analytics or cloud-driven data processes because it will securely manipulate data at the edge of the end device. Edge Computing enables amazing network, compute and storage capabilities for custom manufacturing service platforms and can even be extended to state-of-the-art shopping experiences for clients. For example, Edge Computing can facilitate clients in virtually visiting a digital twin shop floor via AR or VR technology and request unique product amendments based on their requirements and submit it to the core systems of the manufacturing company. Edge Computing can make online shopping experiences and communication so much faster and easier.
Lower Data Latency
Lower Data Latency is one of the most obvious and easily highlighted advantages in Edge Computing because this technology has the potential to reduce data latency rates drastically compared to alternative computing technologies. For example, sending a data action request or requesting for some data from a data centre that is posted across the world and waiting for it to process and come back with responses would take a lot of time, but Edge Computing takes the data manipulation tools close to the data sources; therefore, the data transmission time is chipped down to a few seconds or milliseconds.
When manufacturing solutions are demanding for a mission-critical application, event-driven analytics, and faster insights, Cloud Computing does show many limitations compared to Edge Computing. As a second of time contains a monetary value for manufacturing firms, having low latency is nothing more than an amazing and resourceful advantage, thus, making Edge Computing the apt manufacturing computing mode for data-driven manufacturing establishments.
When manufacturing solutions are demanding for a mission-critical application, event-driven analytics, and faster insights, Cloud Computing does show many limitations compared to Edge Computing. As a second of time contains a monetary value for manufacturing firms, having low latency is nothing more than an amazing and resourceful advantage, thus, making Edge Computing the apt manufacturing computing mode for data-driven manufacturing establishments.
Unfaltering Data Privacy and Security
Data security at the edge is most fascinating and prominently encouraged by data experts because most data tampering, forgery, data piracy and many other data misuse occur during data transmission. Faulty encryption or incompetent security protocols can lead to fraudulent theft of sensitive manufacturing data, but robust cybersecurity offered by edge computation technology does not allow that to happen.
As most manufacturing systems of smart factories are powered by IIoT technology, their number of potential entry points for online criminals has risen. Cybercriminals can breach one point to misuse the whole data system but, if your manufacturing system takes full advantage of the edge to optimise cybersecurity protocols, ensuring the security of your private and confidential data can be less challenging.
A centralised system can also be hazardous and welcoming to online hackers and cyber attacks due to the vulnerability of storing data in a shared point. If computing happens at the edge, like via Edge Computing, your manufacturing systems can expose data to fewer risks and more secured computation.
As most manufacturing systems of smart factories are powered by IIoT technology, their number of potential entry points for online criminals has risen. Cybercriminals can breach one point to misuse the whole data system but, if your manufacturing system takes full advantage of the edge to optimise cybersecurity protocols, ensuring the security of your private and confidential data can be less challenging.
A centralised system can also be hazardous and welcoming to online hackers and cyber attacks due to the vulnerability of storing data in a shared point. If computing happens at the edge, like via Edge Computing, your manufacturing systems can expose data to fewer risks and more secured computation.
A Cost-efficient Approach for Manufacturers
Edge Computing also results in cutting many expenses for manufacturing practitioners. One instance where it saves a little cost, time and effort are during data storage. Manufacturing computation requires a substantial amount of data and storage for data computation. Having extensive storage technologies for manufacturing data can be expensive and inconvenient at most times. But Edge Computing overcomes these limitations because it can ideally store data at the edge. Edge storage is used by manufacturing companies to analyse data locally and only send relevant data to cloud storage after data manipulation. This saves up a lot of space in the backup storage or cloud-driven data storage platforms like Data Warehouses or Data Lakes.
Another instance where Edge Computing financially facilitates manufacturers is in reducing maintenance costs. The enhanced asset maintenance analysis executed by edge computing features allows asset managers to tailor cost-effective and realistic budgets for their asset overhaul efforts and cut down dispensable maintenance costs. The timely asset condition monitoring and predictive insights generated by Edge Computing allow managers to control the risk, cost and performance of their assets single-handedly. With the overall cost of machine maintenance mitigated, and massive ongoing data transfer expenses saved, Edge Computing can save millions of dollars for a manufacturing organisation.
Another instance where Edge Computing financially facilitates manufacturers is in reducing maintenance costs. The enhanced asset maintenance analysis executed by edge computing features allows asset managers to tailor cost-effective and realistic budgets for their asset overhaul efforts and cut down dispensable maintenance costs. The timely asset condition monitoring and predictive insights generated by Edge Computing allow managers to control the risk, cost and performance of their assets single-handedly. With the overall cost of machine maintenance mitigated, and massive ongoing data transfer expenses saved, Edge Computing can save millions of dollars for a manufacturing organisation.
Edge Computing with Cerexio
Cerexio is one of the leading new-age technology enablers in Singapore to offer Edge Computing technology services to the manufacturing sector. Our company uses smart ML algorithms, proprietary streaming technology, AI-driven predictive models, Digital Twins, GIS maps, and a surfeit of technologies that support Edge Computing enormously. If your manufacturing company requires a cost-effective, latency-free, and accurate manufacturing insight generating solution, Cerexio would be the easiest and most unrivalled choice for your company.
Edge Computing is The Future of Manufacturing Computing
Whether it is inventory control, smart machine utilisation, predictive or prescriptive maintenance, or a mere data capture for better analysis, Edge Computing remains to be the most multifaceted technology for manufacturing systems. Edge Computing played a vital role in revolutionising industrial manufacturing to its next best evolution. This technology, combined with other state-of-the-art technologies, becomes the future of manufacturing solutions because time is money for most forward-looking manufacturing practitioners, and Edge Computing saves an ample amount of time in data computations and insight generation. It saves costs, improves efficiency, skyrockets productivity and increases ROI of manufacturing firms, making it a noteworthy and must-deploy technology for all manufacturing giants of the new age. Edge Computing is simply the most required technology for success-guaranteed manufacturing decision-makers around the world.
