Synergy Effect Inc



Trends, Industry 4.0 / IoT / IIoT, Smart Manufacturing, Supply Chain Technology

The manufacturing industry is evolving to comply with Industry 4.0, the  digital industrial revolution. At this crucial junction, we look at  these 6 critical problems that can be resolved using modern technology  in manufacturing.

After steam, electricity, and computers, the manufacturing industry is  looking at another developing trend that aims to change its dynamics  completely – Information. Manufacturing 4.0 seeks to introduce computers  and automation in an entirely different way to the industry. It will do  so by equipping computer systems with machine learning algorithms to  conceive a ‘smart factory’ that generates insights and solutions based  on real-time data. The Manufacturing Leadership Council  has analyzed that this transition will not be smooth. It has listed out  some critical issues that the industry faces in the coming years. This  article will take you through these glaring problems, apart from the  conventional ones, and also present to you how modern technology in  manufacturing can help tackle these issues.

  1.  Widening skill gap tackled by Machine Learning

The ever-growing domains of knowledge and technology require the skill  set of your workforce to stay on pace with global developments.  Alternatively, dynamic algorithms can be built with machine learning  applications to perform complicated tasks that would otherwise require a  specifically trained workforce. E-commerce giant Amazon has tied up with Kiva Robotics to employ about 30000 fulfillment robots in its gigantic warehouses. 

  1. Supply chain complexities managed with IoT and blockchain

Various factors come into play while deciding upon supply chain  parameters such as safety stock levels, delivery schedules, logistics  expenses, etc. Warehouses can use blockchains and Internet-of-Things  applications to make supply chains more efficient and reliable. Volvo currently utilizes IoT and cloud services to improve traceability of its supply chain. 

  1. Disastrous product recalls evaded using AI and simulation

Product Recalls occur due to the inflexible nature of manufacturing  processes that discourages improvisations in products. With the aid of  simulation software and artificial intelligence applications, we can  flex manufacturing processes to correct possible product flaws  dynamically. Digital Twins are now predicting product failures during prototyping. 

  1. Disrupting equipment failure fixed using advanced analytics

Technical failures in machinery can completely disrupt delivery  schedules, thereby damaging reputation. These can also inflate the  maintenance budgets. However, by analyzing historical data of technical  snags using statistical methods employed by big data tools, we can  predict future failures and schedule precautionary maintenance without  hurting delivery schedules. Tata Consultancy Services was hired by an automotive OEM to increase their overall equipment effectiveness which subsequently rose from 65% to 85% using advanced analytics. 

  1. Misleading expectations corrected using modern technology in manufacturing

Industries often fail to meet the stakeholder expectations which are  usually based on historical data extrapolated to present market  conditions. It happens because conventional statistics do not take into  account many other factors such as natural calamities, logistic  disruptions, and political scenarios. Advanced analytics and big data  tools can take into consideration a wide range of factors to provide  more reliable and accurate expectations. 

  1. Mischievous cyber-attacks prevented with AI

Now that the Internet has inevitably penetrated into our industry  systems, we should be wary of potential hackers trying to gain access to  information or control of these systems. Apart from robust firewalls  and layers of security, machine learning and artificial intelligence can  provide a reliable solution to cyber-attacks. Darktrace, headed by  Nicole Eagan focuses on using artificial intelligence to filter suspicious activity from a network. Such systems can detect events such as an ‘inside job’ that antiviruses cannot.  Technologies such as Artificial Intelligencebig dataInternet-of-Thingsmachine learning and blockchain  are leading us to more reliable and accurate solutions to critical  issues. In conclusion, while modern technology in manufacturing may have  been an optional value-added utility before, it is now providing  solutions to the most acute problems in manufacturing.




Original Article by Naveen Joshi/ Allerin/ 2018

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