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Futuristic Tech: Turning the Wheels of Manufacturing

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As 2021 rapidly progresses, the impact of the COVID pandemic on all industries is being felt. Businesses have had to maintain employee/customer distances resulting in the growth of communication-enabled technologies.

The manufacturing industry has also been similarly impacted. While technology has always been an enabler, today, we are beginning to see advancements in ways that interconnect humans with smarter machines for improved processes, performance, and protection.


Wearables are being used in manufacturing to ensure improved safety conditions in work environments. Wearables such as wristbands, smart clothing, or headwear like Google Glasses can provide information to the wearers such as surfaces that are hot, short-circuited equipment, machine malfunction, or even hazardous spills.

Wearable technology for construction workers may also soon help reduce construction worker fatalities and injuries. A U.S. Chamber of Commerce report notes 23% of contractors will be using such technology by 2021.

Wearables are also helping managers gather data that can help towards improving efficiencies and optimization. For example, it may be observed that time is spent by workers using a forklift for short distances between two essential work points, which can be reduced if the floor plan is reworked or eliminated by a conveyor belt.


The manufacturing industry has already deployed IoTs extensively to collect essential production data and turn it into valuable insights. IoTs have helped manufacturers improve operational efficiency and reduce delivery times. The PwC’s 2019 Internet of Things Survey reveals that manufacturers are optimistic about the benefits of IoTs with 68% planning to increase their investment over the next two years.

By deploying enhanced IoTs that are sensor-enabled (audio, video, temperatures, vibration, voltage), manufacturers are now also staying ahead of potential machinery issues and can perform predictive maintenance for improved customer satisfaction.

Recently a Boston-based contractor used an algorithm that analyzed photos from job sites, scanning them for safety hazards and correlated with past accident records. Construction companies can therefore potentially compute project risk and know which projects have higher threats.


While there are still technological, organizational, and regulatory challenges to implementing drones, manufacturers have begun experimenting with drones in warehouse operations and inspection tasks.

Drones are being used to monitor and connect the stages of the manufacturing process, such as moving components to a production line, inspection, or delivery of the final product to shipping. And when regulatory limits are removed, many manufacturers are looking to deploy drones to help them with field inspection and logistical tasks.  


Virtual reality can help manufacturers test and enhance products digitally without creating expensive prototypes, saving time and money.

Automobile manufacturers are already using virtual reality to ensure cars are tested at an initial phase of the vehicle development process, reducing the time and cost involved in ensuring tolerances and safety and altering the design features.

In construction, custom workstations are being built using virtual reality to offer teams immersive design review and collaboration capabilities.

Augmented reality can be used to monitor field conditions, measure changes, and help manufacturers envision a finished product.


Industrial robots have been speeding up manufacturing operations for the past decade. In fact, in another recent PwC report, 59% of manufacturers are already using some form of robotics technology.

Today, however, we are beginning to see more AI-enabled robots that collaborate with human workers. The Tesla Gigafactory uses smart self-navigating, Autonomous Indoor Vehicles (AIVs) to shift goods between workstations.

Companies like Cornell Dubilier, a power capacitor manufacturer in the US, also use ML-trained robots to inspect capacitor installations, doubling its speed of labelling process from 125 parts an hour to 250 parts an hour.


AI and machine learning make it possible for manufacturers to improve processes and products through intelligent feedback, which the algorithm can constantly learn from. According to Deloitte, machine learning improves product quality up to 35% in discrete manufacturing industries.

Even the construction industry (considered one of the most under-digitized industries in the world) uses AI to predict cost overruns based on project size, contract type, and the competence levels of project managers. AI-driven cameras also help construction workers avoid spending hours walking around searching for tools, as AI can immediately recognize and locate on-site tools and equipment.

Advanced machine learning systems offer smarter decision-making capabilities to manufacturers and can improve tasks such as research, development, and product line extension.


While advances in 3D printing have helped streamline prototyping, one of the most encouraging outcomes is its potential for mass customization.

The 3D printing industry is projected to reach USD 63.46 billion by 2025 and is offering manufacturers the ability to innovate through its introduction of new materials. Unbelievably, 3D printing also offers builders the ability to produce entire houses!

Start-up 3D printing construction company, Icon says that 3D printing can reduce construction costs by up to 30% and produce a home twice as fast as traditional methods.


The adoption of sensors and connected devices have resulted in a tremendous increase in the data points being generated for the manufacturing industry.

Only by applying advanced big data analytics, can manufacturers use this vast information to discover insights and identify patterns. When properly deployed, analytics can help manufacturers improve processes and supply chain efficiency and predict the variables that could adversely affect production.

Additionally, big data and analytics can be applied to assess damages in buildings and fraud detection. Fraud analytics using machine learning to prevent contractors from making false claims by analyzing images against existing claim databases. This is particularly useful in construction such as roofing, which needs to be viewed from above and can easily be faked. Advanced analytics can automate the processing of roof condition and minimize the need for aerial imagery which be expensive, time-consuming, and unsafe.


Successful manufacturers are often the businesses that can orchestrate and align all the facets of their operations smoothly. Therefore, the use of technology in manufacturing is mainly driven by their need for better efficiency and control over the manufacturing process.

Advances in technology such as improved connectivity, analytics, AI, and robotic deployment are geared more towards offering incremental improvements than creating disruption. And manufacturing businesses that are not considering technology to improve their efficiency, efficacy, and business agility will be left behind.









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