Cybersecurity in Manufacturing:
How can factories manage data security risks with Smart technology?

The importance of cybersecurity in manufacturing

Does this sound like you?

After intense negotiations with dozens of vendors, grueling engineering discussions with the production team, painful budget approvals, and months of redrawing the assembly lines, you moved your semi-automated production process into something contemporary. Your modern world-class manufacturing line is now a text-book case of how a connected Industry IoT plant should look: you have robotized processes, IoT asset management, automated vendor plug-ins, remote monitoring and control of most production routines, vision managed defect assessment, and a holistic view of how your other plants halfway around the world are functioning -all in a single screen, with a few clicks.

Now that you have slashed defect rate cut down human intervention, and improved production rate, you think you have got it all figured out and can take that over-due holiday on the beach? Right?

Wrong.

Sorry to be dramatic. But this is what the cyber bots are heard saying: “Thank you for creating a fertile territory for us to proliferate. We couldn’t be luckier”.

Speed is only half the battle in IIoT

The ‘Floating assembly lines’ of industrial revolution 4.0 are designed to meet demand in the shortest time possible. Approved supplier systems automatically log in and ship components to a live assembly line to meet the production targets of an OEM producer. Most of these decisions are made by systems using a variety of software (AI, IoT hub, decision algorithms), learning systems (M2M), networking (IR, 5G NR. Cloud computing), and production systems (3D printing).

Consider the possibility that a supplier’s system is infected with malware and enters this system. It could proliferate the OEM supply chain, other supplier systems, and respective corporate IT infrastructure in minutes. The potential for damage is even more significant if, by some means, it mutates and destroys safety mechanisms in the plant and endangers human lives.

According to the Deloitte and Manufacturers Alliance for Productivity and Innovation (MAPI) study, 48% of surveyed manufacturers fear that cyber attack is a real threat and the greatest danger they envisage for smart factories. And damage due to a cyber incident in manufacturing was estimated to be about $330K.

Disconnected islands in a sea of connectivity

The single biggest threat appears to come from here: Operational Tech (OT) and Information Tech (IT) systems do not talk to each other. OT refers to hardware and software used to change, monitor, or control physical devices or processes within a production facility.
Traditionally, manufacturing systems have been proprietary with few, if any, open standards for third-party plug-ins.

Tightly coupled legacy systems become a natural barrier for easy upgrades imposing change-impact study for every minor upgrade. Security controls for such systems are vendor-driven patches that are slow to come by. Also, vendors of traditional manufacturing systems do not cover OT in service agreements and maintenance contracts. The IT team simply believes that ‘all is well as they focus on the rest of corporate ERP, DB, networking, and productivity systems.

Some important cyber security considerations for the manufacturing facility are detailed below:

  • Solution Design: Restrict device and system access to authorized personnel only. Ensure cloud or network access follows rules-based access control.
  • Access & Authorisation: Ensure default passwords are changed in all IIoT devices, the new passwords conform to IT Security policy, and access control of edge devices is regulated. Default password vulnerabilities in 3rd party connected devices are a leading cause of security vulnerability.
  • Production Planning: Ensure company-wide secure remote access policy is defined, followed, and documented. Ensure cyber intelligence information exchange, record incidents, document phishing attempts, and develop thwart methods.
  • New Technologies: 3D printing and enhancements to the existing production line should be zoned separately with one-step isolation. For network 3D printers, it may be required to run separate cyber assessment tests and share reports with corporate IT security teams.
  • RPA, ML, NLP, and AI: These new technologies have clear benefits on the shop floor but will bring in their threats. Deploy rigorous application whitelisting, access control, portable memory control (USB drives moving in and out), controlled access to the internet on such systems, and accurate real-time inventory management.
  • Asset Management: Ensure security rules and policies are risk-based rather than compliance-based. Maintain a qualified, dedicated team to create surprises in addition to routine checks. This team should be aware of company-wide incidents and trained to observe seemingly unconnected events to extract real intelligence in a security scenario.

Since digital and cybersecurity elements will become all-pervasive sooner or later within corporates, it is a matter of time before they start impacting manufacturing processes.

Conduct a thorough cybersecurity assessment

This is an independent exercise and should not be downplayed in a regular corporate IT security audit. Ideally, the cyber assessment should be done every six months, including OT in the IIoT environment, recorded results, gaps plugged, shared with corporate IT and cybersecurity intelligence groups in the industry for mutual benefits.

It is also advised to build security protocols across the corporation, cover micro-assets and entry points for physical and digital products, and make sure the protocols are part of an overall security umbrella policy applicable to all branches and personnel.

In conclusion, remember that internal view often leads to fatigue derived from familiarity. It helps tap the rich experience of industry experts who have already done some of these things.

For example, at Trigent, our industrial security experts have delivered solutions in RPA (complementing human judgment with automation-led efficiency), predictive maintenance, and AR (Augmented Reality – helping find unique ways to connect humans and machines) for big and small manufacturers. Our clients across energy and oil, retail and manufacturing, healthcare, and education stand testimony to our capabilities.

Give us a call or drop us a line. We will be happy to help.

Underlying challenges manufacturing enterprises face during cloud migration

Cloud migration has increased enormously as manufacturing companies gain and maintain a competitive edge. A fundamental paradigm shift in planning and orchestrating business models is required. Manufacturing companies need to ensure that management and IT teams work together to build a product and cloud service portfolio that complement each other and are aligned for operational excellence. 

Although manufacturing companies produce tons of data, the irony is that there isn’t enough information. Manufacturers find transformation difficult since equipment lasts for decades, and replacements are costly. They tend to have siloed data that sits in a data lake before being used appropriately. When interconnected, they struggle to deal with unstructured data and the process required to scale that solution across the enterprise. Many manufacturing companies are now addressing this issue with an edge platform.

Jabil1, the manufacturing solutions provider, quickly addressed the data problem. Its plant floor quality assurance solution organizes data to analyze issues in real-time and offers a high prediction accuracy rate. With an ability to identify errors even before they occur, Jabil sees substantial productivity improvements. 

While young companies may find it easier to hop onto the Cloud, large enterprises often find themselves struggling under the weight of legacy IT systems that are somewhat rigid and may require more extended transition periods. 

We aim to uncover ways to circumvent these issues to ensure quick transitions and faster cloud success.

Implementing the right strategy ensures a successful migration to the Cloud. Let’s discuss

The state of cloud migration in manufacturing

As per a recent survey, the number of companies using cloud technologies as part of their digital transformation endeavors has increased from 51% in 2019 to 62% in 20212. During this time, edge computing deployments grew from 43% in 2019 to 55% in 2021, while fog computing, known for its capabilities to create a small, cloud-like computing infrastructure, rose from 20% in 2019 to 25% in 2021. 

The jump is not surprising because manufacturing processes require real-time control and response rate to operate and support efficiently while checking on downtimes. Cloud helps in remote monitoring, collaboration, and building a data-driven culture. 

A classic case in point is UNOX3. Its pursuit of creating ‘intelligent’ ovens took the cloud route to develop new cutting-edge projects for data-driven cooking. 

UNOX has revolutionized its customer service via an omnichannel cloud contact center that enables it to meet 95% of service-level customer requests efficiently compared to just 67% before cloud adoption. A managed live streaming service to create interactive video experiences and a content delivery network service to deliver content and applications with low latency and high transfer speed has helped it improve agility, scalability, and savings.

In the wake of the pandemic, remote monitoring compelled manufacturing companies to migrate to the Cloud. It allows them to create key performance indicators and enables plant floor managers to closely watch asset utilization and OEE (Overall Equipment Effectiveness). 

Automation technology supplier Emerson for instance, witnessed a surge in the use of sensors combined with edge gateways when manual on-site inspection became difficult. Explains Peter Zornio, chief technology officer at Emerson, “Previously, people were looking into automating some manual inspection with sensors and edge gateways but held back because they thought it was too expensive. But suddenly, without enough people on site to do inspections, the technology presented them with a way to move forward.”

While everyone is sold on the idea of migrating to the Cloud for its apparent benefits like flexibility, agility, enhanced privacy, security, and greater operational efficiency, the struggle to migrate successfully to the Cloud is real and overwhelming for many. In manufacturing setups, systems are usually interconnected with the plant equipment, leading to roadblocks on the way to cloud adoption. 

However, there are ways and means to avoid them. 

Create a robust cloud migration strategy 

The right cloud migration strategy based on a thorough assessment of your needs and resources can be a good starting point. 

Core Technology Molding Corporation, known for its highly engineered plastic products and tooling designs, has been able to keep operations running smoothly with a cloud-based ERP system. It allowed the company to address its need for monitoring processes in real-time when employees were forced to work from home.

The one that’s most appropriate for you should be found on the following considerations:

  • What are your business goals? What problems are you trying to resolve?
  • In which stages of production are downtimes most damaging for business? 
  • What are your security, regulatory & data privacy requirements?
  • How equipped are you to tackle disasters to ensure business continuity?
  • Are skills & experience internally available to undertake a cloud migration project?

Your cloud migration exercise has to be driven by a purpose. You need to identify the pain points to understand what could work for your business. 

Assess your cloud readiness

Cloud readiness is not just limited to tools and platforms but includes people and processes too. The digital literacy of your employees is crucial for successful cloud adoption. Cloud providers offer advanced tools, testing, and interface options to enable agile development in a typical manufacturing IT environment where the cost of experimentation and failure is extremely high. With hundreds of applications spread across multiple physical data centers in diverse geographical locations, fragmented IT poses a considerable problem. 

Cloud can enable standardization of infrastructure and platform to recover quickly from outages. Suntory Group, a Japanese multinational brewing, and distilling conglomerate, adopted AWS cloud to standardize their infrastructure and systems. The decision was part of its global expansion plan to accelerate processes following a merger or acquisition and reduce operational burden. The Group reduced infrastructure TCO (Total Cost of Ownership) in the Japan region by 25% soon after cloud adoption.

Manufacturers need data to forecast demand, expedite orders, check the quality, and predict equipment failures in real-time. They need to break data silos and make informed decisions to increase production capacity and improve the supply chain. They need a 360-degree view of the data to get deeper insights. Going beyond the mere ‘life and shift and wait’ approach is essential to gain greater sovereignty over your data.

Siemens, the manufacturing giant, has been leveraging Google Cloud’s data cloud and AI/ML capabilities to implement artificial intelligence at scale. By harmonizing the factory data, employees working on the plant floor can visually inspect products and predict the wear and tear of machines on the assembly line.

Collaborate with the right technology partner

Applications and Data cannot be moved overnight and will cause security concerns if you overlook the migration time that would be required. It’s therefore essential to have a meticulously crafted roadmap based on priorities, business goals, timelines, resources, and budget. 

While everyone understands the importance of cloud adoption, a whopping 74% fail to capture its total value, according to McKinsey’s recent Cloud in Discrete Manufacturing Industries survey4. 50% of respondents have found cloud technology more complex than they had perceived it, while 40% admitted to exceeding their cloud budgets.

Choosing a migration partner based on familiarity or low pricing can lead to migration failures that can be too expensive to rectify. While iterating ways to budget cloud migrations, Gartner5 points out that 60% of infrastructure and operations (I&O) leaders will experience public cloud cost overruns through 2024, putting a big dent in their on-premises budgets.

The role of a technology partner is highly critical here. 

The right technology partner will evaluate the complete ecosystem, review the interdependencies across siloed applications, and prioritize the workloads to be migrated. They will offer a comprehensive cloud strategy to enable successful cloud adoptions without impacting business users and service-level agreements. They will have the tools and resources to move multiple, complex applications. 

They will help you adopt the Industry 4.0 framework with appropriate automation tools and cloud-based data analytics. With real-time visibility into the manufacturing ecosystem, they can empower you to build more innovative products and create value for your customers and business partners.

Ensure migration success with Trigent

Allow us to help you migrate smoothly to the Cloud and manage your manufacturing workloads with ease. Our technology experts can help you with cloud-native applications and advanced data analytics solutions to achieve agility at scale. 

Our cloud strategy has been helping our clients get maximum business value. We can help you too. 

Call us today for a business consultation.

References

  1. https://cloudblogs.microsoft.com/industry-blog/manufacturing/2017/10/11/digital-transformation-excellence-lessons-from-manufacturing-leaders/
  2. https://www.automationworld.com/TakeFive/video/21977710/how-industry-is-using-cloud-edge-and-fog-computing-today
  3. https://aws.amazon.com/solutions/case-studies/unox/
  4. https://www.mckinsey.com/industries/automotive-and-assembly/our-insights/clearing-the-air-on-cloud-how-industrial-companies-can-capture-cloud-technologys-full-business-value

Effective Predictive Maintenance needs strategic automation and human insight

New-age technologies like Artificial Intelligence (AI), Machine Learning (ML), Internet of things (IoT), and predictive analytics are automating processes and augmenting human capabilities. Together, they set the stage for innovations in different sectors. Manufacturing is leveraging Predictive Maintenance (PdM) that takes preventive maintenance several notches higher.

What is Predictive Maintenance?

PdM changes the approach from reactive to proactive maintenance, empowering enterprises to anticipate changes in the system and preemptively manage them. In other words, it helps enterprises predict and avoid machine failure and resultant downtimes. These analytics-led predictions optimize maintenance efforts and facilitate frictionless interdependence.

According to Deloitte, PdM increases equipment uptime by 10-20% and reduces overall maintenance costs and maintenance planning time by 5-10% and 20-50% respectively. With a CAGR of 25.2%, the global predictive maintenance market is set to grow from USD 4.0 billion in 2020 to 12.3 billion by 2025. The growth is fueled by the continued demand for reducing maintenance costs and downtime.

In the current Industry 5.0 environment, the role of maintenance has evolved from merely preventing downtimes of individual assets to predicting failures and creating synchrony between people, processes, and technologies. Predictive maintenance plays its part well, though it does bring along certain challenges that necessitate human intervention.

Benefits of predictive maintenance in manufacturing

As mentioned earlier, predictive maintenance helps eliminate unplanned downtime and related costs. In an IoT-driven world where sensors, devices, systems, etc. are connected, McKinsey believes that the linking of physical and digital worlds could generate up to $11.1 trillion annually in economic value by 2025.

Maximized runtime also means better profits, happier customers, and greater trust. Predictive maintenance can ease logistics by choosing maintenance time slots outside of production hours or at a time when the maintenance personnel is available. It contributes to supply chain resilience, material costs savings, and increased machine lifespan.

However, PdM is only as good as the data it relies upon. Due to IoT technology, data comes from different sources and needs to be duly analyzed before it can be harnessed to make predictions. Hence the importance of IoT Predictive Maintenance

Limitations of predictive maintenance

We need to consider several elements to translate the information PdM provides into positive outcomes. For instance, depending on usage and maintenance history, it may advise you to replace a certain part or component. But this information can lead to further questions. You may need help in deciding which brand and vendor to consider, whether replacement of the component is a good option, or would it make better sense to replace the equipment entirely.

The forecast is often prescriptive and based on statistical models. While optimizing the operational efficiency of a particular line of business, PdM often fails to consider how it impacts other lines. For instance, when it suggests particular equipment is due for maintenance, it may not be able to offer advice as to where the production/processing needs to be shifted when it’s down. The value it offers will therefore be shaped by how decision-makers respond to predictive data.

Data quality and coverage are critical to make predictive maintenance work for the organization. For data to be suitably collected, integrated, interpreted, and transformed, we need dashboards, notification systems, and a bunch of other things to get started. This requires considerable research and planning to go into its implementation for it to start providing the insights we need.

Predictive maintenance use cases in manufacturing – The key lies in the way you respond

Decision-makers typically respond to predictive data with either hypothesis-driven or data-driven responses. The former stems from past business experiences and determines the plan based on a limited scope of response actions. Data-driven responses, on the other hand, aim to find solutions based on real-time business realities and consider several optimization scenarios to determine the way forward.

In contrast to hypothesis-driven decision-making, optimization ensures that all possible paths are explored and evaluated, relevant constraints are taken into consideration, and cross-functional interdependencies are looked into. A workable scenario based on business realities is thus created with no scope for purely intuitive responses.

Despite the analytics-driven insights, predictive maintenance is incomplete without human judgment. Smart decisions come from the ability to visualize the physical and financial outcomes before enforcing them. High-risk situations might arise, and thus they are best left to human discretion.

A predictive maintenance model for Industry 5.0

Manufacturers need clarity on several variables to understand the implications of failure. A false alarm triggered due to inaccurate predictions can result in a lot of unwarranted chaos and anxiety. However, a missed detection might often prove to be a costly error, sometimes resulting in loss of humans and property. Therefore, while understanding variables, they need to first know how often the variable behaviors occur on the factory floor. Strong domain knowledge along with solid data based on previous failures and scenarios is the key to understanding a machine.

Prediction accuracy will improve if we have adequate data on the behavior of machines when they are very close to failure. Only skilled personnel can determine this; some data sets, despite being important, are harder to collect and yet very critical for decision-making.

If we need data on a machine that breaks just once in a year or two, we need to work closely with machine makers who already possess a large pool of relevant data. Alternatively, we may choose to create a digital or a simulation model to create relevant data sets. The most expensive failures are usually the ones we never expect and hence relevant testing for different scenarios should also be considered.

The future of predictive maintenance

The way forward into Industry 5.0 is to create a predictive model that uses analytics, machine learning, and Artificial Intelligence (AI) in conjunction with human insights.

Manufacturers are now relying on predictive models to facilitate smart manufacturing as they struggle with quality issues more often than machine failures. Unusual temperatures, random vibrations, are all telltale signs that a machine may be in dire need of maintenance. Simple data sets can be a good starting point as we scale up with the right predictive maintenance solution. But, in the end, it’s the human insight that can give predictive maintenance its winning streak.

Predict business success with Trigent

At Trigent, we are helping organizations benefit from Industry 5.0 We help them build value with predictive analytics and rise above maintenance challenges. With the right guidance, we help them foster the man-machine symbiosis to harness new levels of operational efficiencies.

Call us today for a consultation. We’d be happy to help with insights, solutions, and the right approach to predict better business outcomes.

6 Most Popular RPA Use Cases in Manufacturing Industry post-COVID

The role of RPA in manufacturing post pandemic

As markets continue to grapple with challenges posed by the pandemic that shows no signs of receding, organizations are now pinning their hopes on technology with robotic process automation (RPA) that can take care of repetitive routine tasks. RPA ensures tasks that earlier required days and weeks can now be completed in a matter of just a few hours or minutes.

The benefits of RPA use cases in manufacturing industry include better productivity, efficiency, accuracy, less wastage, and greater focus. No wonder almost 80 percent of global corporate executives that participated in the Deloitte LLP survey1 last year agreed to have implemented some form of RPA in their organization while 15% said they planned to do so in the next 3 years.

Expected to grow at double-digit rates through 2024, the global RPA software revenue is predicted to touch $1.89 billion in 2021 indicating a whopping 19.5% surge from 2020.

The pandemic has fueled enterprise interest in RPA as Cathy Tornbohm2, distinguished research vice president at Gartner explains, “The decreased dependency on a human workforce for routine, digital processes will be more attractive to end-users not only for cost reduction benefits but also for ensuring their business against future impacts like this pandemic.”

RPA is making great strides in diverse sectors including manufacturing. Applied Materials Inc., a Santa Clara, California-based company, has begun using bots to automate different areas of financial accounting for increasing productivity and plans to have 255 bots to improve workplace processes.

Top 6 RPA use cases benefitting the manufacturing industry

1. Bill of Materials (BOM)

Employees rely on a lot of information when it comes to the development of new products and commodities. They need to have the exact details as to what to purchase and when, the vendors/dealers that need to be contacted for the purchase, and how to go about the purchase.

Surge Transportation leveraged our expertise to create a pricing engine that offers real-time pricing to stakeholders based on a predefined strategy. The strategy can be modified in the application custom-built for them. RPA facilitates the set up of automatic alerts for changes in the system, thus improving regulatory compliance and supply chain performance. This makes our client stand tall among the top 1% of competitors to have this capability.

Also Read: Automating pricing operations enables 3PL to grow revenue by 40%

2. Data Migration

IoT equipment is now an essential part of the manufacturing fabric. But the challenge comes from the fact that legacy systems are ill-equipped to share data with others within the manufacturing ecosystem. RPA comes to their rescue in achieving this complex and time-consuming feat since bots can work independently of APIs.

RPA integrates different applications by acting as an intermediary between the old systems and the new thus facilitating seamless data migration. What makes RPA so empowering is its ability to correct and fix inconsistencies along the way in real-time. Insurers have leveraged RPA to lower its onboarding costs by 91% even as it experienced a 600% improvement in processing time. In turn, this boosted its service quality and customer experience that was held back by backlogs previously.

3. Customer Care and Service Desk Support

Delayed response or long resolution times can harm the trust you have built with your customers. To be able to help them promptly in real-time, you need to swiftly navigate through multiple business systems which are often laborious. But things can change dramatically by automating customer service with RPA.

US banks have harnessed RPA to improve their average handling time at their customer service center by 30%. This resulted in a monthly savings of 8000 work hours, enabling employees to use the freed time on value-added services.

4. CRM and Sales Order Integration

While sales thrive on relationship building and communication, it is a known fact that sales order integration does not stop there. It involves a mix of activities like creating estimates, checking product availability, processing orders, managing logistics, etc. Not to mention the coordination between many departments these processes call for.

Also Read: How automation is improving order and inventory management in logistics

A restaurant group used RPA to automate sales reports resulting in a 65% decrease in daily time expended on generating reports from across over 40,000 locations. This helped them nurture customer relationships and increase sales revenue.

5. Regulatory Compliance

The safety protocols constantly evolve in the manufacturing domain. There are individual product regulations to look into along with a whole lot of compliance requirements to adhere to. RPA takes away the stress from regulatory compliance ensuring your manufacturing outfit is audit-ready with accurate data processing and detailed records.

All bot activities are constantly monitored and available for inspection through a central log. RPA enables quick and effortless process updates too so that you are always up-to-date when it comes to compliance regulations.

6. ERP Automation

Bots play a big role in invoice processing and inventory control both of which involve elaborate paperwork, identifying deficiencies, and fulfilling customer demand at the earliest. Due to its ability to enhance operational efficiencies, RPA gives manufacturers an edge to manage tasks like sending invoices, creating purchase orders, computing shipping costs, taxes, or discounts, and driving overall financial processes that would otherwise require a high level of human intervention.

There are a whole lot of reports that need to be created and sent out via email or to be uploaded in a shared folder. SKUs need to be updated regularly too and Accounts Payable and Receivable have to be accurately managed. RPA takes care of all the reporting and related administrative chores to help organizations manage their business requirements efficiently.

The role of RPA is undeniably critical in the present manufacturing landscape. As Fabrizio Biscotti, research vice president at Gartner points out, “The key driver for RPA projects is their ability to improve process quality, speed and productivity, each of which is increasingly important as organizations try to meet the demands of cost reduction during COVID-19.”

Discover the impact of RPA with Trigent

Our RPA services are built for speed and scale. They make you agile to adapt in a fast-changing manufacturing sector and enjoy extraordinary cost savings along the way. We can help you minimize production downtime, optimize processes, and enhance your operational capabilities.

Our highly experienced business process consultants are eager to talk to you to help you automate with RPA without needing you to navigate through robot complexities.

Call us today for a business consultation.

References

  1. https://www.wsj.com/articles/software-bots-multiply-to-cope-with-stretched-resources-11611615504?mod=djemCIO
  2. https://www.gartner.com/en/newsroom/press-releases/2020-09-21-gartner-says-worldwide-robotic-process-automation-software-revenue-to-reach-nearly-2-billion-in-2021#:~:text=RPA%20Market%20Forecast%20to%20Grow,latest%20forecast%20from%20Gartner%2C%20Inc.

6 Examples of how Augmented Reality (AR) Transforms Manufacturing

Remember how the IKEA Place app allowed us to experience what it would feel like to have their signature pieces in our homes? Pokémon Go sent the younger demographics on a wild chase even as it gave the world a taste of what Augmented Reality (AR) technology can do.

The world of humans and machines is intertwined and symbiotic today. The reality around us has always been three-dimensional but for decades our understanding was based on two-dimensional pages and screens that fell short of what we wanted to know. Until Augmented Reality started narrowing the gulf between the real and digital worlds.

Such is its demand that MarketsandMarkets1 predicts the global augmented reality market to grow to $77B by 2025 from $15.3B in 2020 at a CAGR of 38%. From an estimated 598 million devices by the end of 2020, the number of AR active devices is expected to touch 1.73 billion by 2024.

AR is the convergence of the digital and the real world. AR has become mainstream and is being leveraged in all areas including manufacturing.

As demand for remote assistance and collaboration from enterprises continues to rise, AR-based apps are now being extensively used for monitoring, identifying, and fixing technical issues. They also play a pivotal role in various areas of manufacturing such as designing, retrofitting, assembling, manufacturing, repairing, etc.

Equipped with AR wearables, the manufacturing workforce can now achieve feats that were previously unthinkable. Here’s a sneak peek into the many roles this tech plays in empowering the manufacturing industry.

1. Offers Live Support and Equipment Maintenance

Caterpillar Inc. used an innovative augmented reality-based live support video calling platform to take its commitment to provide remote assistance to the next level. This helped technicians perform service and maintenance checks while taking pictures, having live support, and getting step-by-step instructions to complete a task.

AR enables customers, dealers, and technicians to interact with products and visualize 3D renderings of equipment, and collaborate in real-time. In the new normal of contactless interaction, AR presents the perfect solution to enterprises to offer expert support to their customers anywhere in the world. This not only saves time and effort but minimizes downtime significantly.

AR also helps identify problems and errors that may stop machines and equipment from working optimally. Mitsubishi also offers maintenance support using AR wherein technicians wear smart glasses to check the order of inspection of items on AR display and records results with voice entries. This method comes in handy in noisy environments and eliminates manual errors.

AR takes away the guesswork from maintenance and ensures methodical response and faster recovery time. AR devices enable the maintenance team to instantly see all the details such as operation times, date of the last service, potential points of failure, etc.

2. Facilitates Product Design and Development

The augmented reality when used for product design can accelerate workflows, reduce costs, and infuse precision. While we are familiar with prototyping, AR allows developers to evaluate concepts even before the prototyping stage with a concept called ‘pretotyping’. It allows them to critically evaluate product variants and ascertain if they are indeed building the right thing with the required precision. Explains Brenden Monahan CPO at Vusar, “Faster failings result in even more successes and also fewer missed chances. With AR your initial prototype could be your last.”

NASA too has utilized AR to speed up the construction of the Orion spacecraft while its Mission to Mars2 AR app is giving users a virtual ride to the Martian planet. With AR, it’s almost akin to seeing a product being designed and built-in real-time. Design teams can collaborate, deliberate, and offer insights to eliminate the tedious back and forth communications and iterations. With AR, manufacturing companies are now able to reduce turnaround times as well as delivery times.

3. Aids Complex Assembly

Boeing – the world’s leading manufacturer of commercial jetliners – managed to cut production time by a whopping 25% with a nearly zero error rate using AR technology to wire hundreds of planes. As Randall MacPherson, senior manager of Boeing’s Electrical Strategic Fabrication Center in Mesa, Arizona puts it, “We’ve seen significant productivity increases in our wiring harness facility from this technology where we’ve tested it, and it resulted in a substantial improvement to first-time quality. Wearable technology is helping us amplify the power of our workforce.”

AR is now being used by pretty much all modern manufacturing companies that need to put together a zillion pieces in complex assemblies at the speed of thought. There are assembly instructions to adhere to that can now be seen in the work field in real-time during conception as well as maintenance phases of manufacturing.

4. Ensures Quality Control

AR with its ability to overlay the real world with digital data helps manufacturers conduct quality control processes with precision. It informs technicians about defective product components and whether product components meet quality parameters with quick inspections. The findings can be further compiled in precise reports for future reference.

Automobile giant Porsche has already implemented AR to test processes in real-time, conduct quality audits with suppliers via video conference, and subsequently set new quality benchmarks. AR gives technicians a decisive advantage to analyze performance, compare systems, and detect deviations. Incorrectly installed parts can be visualized while missing parts can be identified. The results obtained using AR help manufacturers save time and live up to their promise.

5. Streamlines Logistics

Every time a customer places a new order, certain procedures need to be followed. From checking the inventory to scanning the product, to preparing it for delivery to actually delivering it – there’s an elaborate process involved. But with AR, it’s easy and quick. In fact, AR proved to be quite a game-changer for DHL that set new standards in order picking by allowing its workers to see things like picking instructions, locations of items, and exact placement on carts through head-mounted displays.

DHL claimed AR implementation in warehousing operations helped improve its picking process by 25 percent. Hands-free order picking has helped increase productivity and has played a big role in improving operations during transportation, last-mile delivery, and a host of value-added services that allow them to collaborate better with their partners and make their customers happy.

6. Aids in Training and Upskilling Employees

Often, putting someone new on the floor can lead to safety concerns since they are unfamiliar with the protocols and equipment. But AR ensures they can be trained without any compromise on safety by explaining the ‘why’ and ‘how’ pertaining to their jobs. AR-enabled apps can offer complete visibility that helps trainees to get hands-on experience.

With AR at the helm, trainees do not have to struggle with manuals all the time. AR works alongside to help them even in the most challenging environments providing them step-by-step guidance to understand documents, manuals, and other work-related stuff. This helps them get hands-on experience along the way.

Jaguar Land Rover (JLR) too leveraged AR in collaboration with Bosch to train their employees with a technical training app that digitally visualized an X-ray into the Range Rover Sport vehicle dashboard. Manufacturers are now using AR even for upskilling to boost the abilities of production workers for better performance, safety, and worker satisfaction.

Give your business the AR edge with Trigent

AR is helping the manufacturing sector improve productivity, decrease costs, and ensure a higher level of safety.

At Trigent, we have been connecting humans and machines through AR for many years now. Our highly proficient team can empower you with customized solutions to help you in diverse areas of manufacturing including production, maintenance, training, and QA.

Call us today to know more.

References

  1. https://www.marketsandmarkets.com/Market-Reports/augmented-reality-virtual-reality-market-1185.html
  2. https://www.travelandleisure.com/trip-ideas/space-astronomy/mission-to-mars-augmented-reality-app

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