Tag Archives: Artificial Intelligence

 

Warehouse operations are critical to any manufacturing business. From holding inventory to delivering items, the process must be as swift and efficient as possible. Earlier practices such as document management and communication have been a significant step, but growth and progression in the supply chain call for more.

The rise of the Internet has been a key event in improving warehouse operations. As technology progresses, there are even more ways to optimize the supply chain, and ensure every item or employee is included.

The Need to Streamline Warehouse Operations

Warehouse operations offer many opportunities for error while meeting tight deadlines. Brand owners must recognize these areas for improvement and see what can be done to reduce mistakes. Streamlining translates to more accurate and faster processing, which equates to higher customer satisfaction.

Warehouse operational efficiency also translates to long-term time and cost savings. Next-gen technology can streamline warehouse operations using fewer minutes and dollars resulting in increased productivity.

Remember to include workers when integrating these new electronics. Forty-two percent of workers fear job loss from automation and new technologies. However, the reality is humans are responsible for tool management and strategy execution. Train them to work with these items rather than against them.

Vital Next-Gen Technologies in the Warehouse

Some facilities may incorporate multiple next-gen technologies, while others only incorporate one. The most important factor is to assess what works best for a specific set of operations and makes sense investment-wise.

Automation and Robotics

Certain warehouse operations are rather repetitive. It can be the same cycle of picking out a product, packing it, adding a shipping label and sending it off. Automating these processes with robots can take care of these mundane tasks, shifting focus to more pressing concerns in the facility.

Smaller establishments can still find ways to introduce automation. For example, installations like conveyor belts move items along the facility. Automated labeling machines can transfer the necessary information.

Certain equipment can also improve staff safety. For example, about 70 worker fatalities occurred in forklift-related accidents across different sectors. Self-operating forklifts simplify warehouse transportation and prevent hazardous contact.

Blockchain Technologies

Blockchain technology is a key database streamlining data storage and information sharing. Warehouse management entails plenty of information about product quantity and delivery. Many parties — like suppliers, manufacturers and distributors — are involved.

The blockchain ensures information is accessible and interconnected. What’s ideal about this next-gen ledger tech is it keeps data under wraps. Each block is secure in nature because it requires verification and permission.

Thus, blockchain technology is ideal for various financial transactions. If a distributor pays a manufacturer for production, they should process the transaction through this network. It has a suitable layer of encryption while executing those actions.

Internet of Things

The Internet of Things (IoT) is a flexible alternative to blockchain technology. By employing this network, a warehouse can generate connections between products and machines through sensors and software. If one product is removed, the system will detect it and send an update.

The IoT enables warehouses to receive real-time data about the movement of their shipments. This cuts down the slower steps in inventory management and prompts communication between devices so all parties in the supply chain can stay up to date.

It is possible to fuse both next-gen technologies in warehouse operations. The blockchain establishes trust, while the IoT improves connectivity, refining the process of sharing information among multiple parties.

Artificial Intelligence

Multiple industries are utilizing artificial intelligence (AI) in business processes. While most people find its use helpful in customer service, 40% of business owners use AI for inventory management and 30% for supply chain operations. Warehouses can use their programs to collect and organize data in the long run.

AI can also generate different presentations and reports based on the data it receives. Manufacturers with multiple facilities can upload their information and send a prompt to receive specific information about their inner workings.

AI can also provide business recommendations on streamlining operations with predictive analytics. However, these programs’ output depends on the data set given, and there are limits to the predictions they can make depending on the amount of variation.

The next best thing to do with this output is to conduct a comprehensive data analysis. Use the information to set metrics for evaluation in the future. If one area is faltering, make actionable decisions to influence processing in the facility.

Cybersecurity

As effective as next-gen technologies in warehousing are, new problems arise. The Identity Theft Resource Center found supply chain attacks impacted more than 10 million people in 2022. Each facility and its streamlined performance are vulnerable to these cyber threats.

Focus on preventive measures to maintain the order of operations. Investing in a firewall adds a layer of protection to warehouse information. Add intrusion detection systems to alert business owners of any breaches.

Physical security installments can also protect warehouses. For example, surveillance cameras log who accesses company computers during and outside active hours. Biometric technology is also a good touch for tracking and access control.

Optimize Warehouse Operations with Digitalization

Speed and effectiveness are crucial in warehouses. Next-gen technologies have made great strides in equipping facilities with these attributes, so take advantage of them to strengthen operations.

*This article is written by Jack Shaw. Jack is a seasoned automotive industry writer with over six years of experience. As the senior writer for Modded, he combines his passion for vehicles, manufacturing and technology with his expertise to deliver engaging content that resonates with enthusiasts worldwide.

Back to top ↑

 

Automobiles are becoming smarter thanks to advancing technologies and manufacturing practices. Nowadays, vehicles can communicate with each other, people and networks to increase safety due to artificial intelligence (AI) and machine learning (ML). What if cars on the road could communicate with everything? This technology is in the works through vehicle-to-everything (V2X) communication. Here’s a guide on V2X, its benefits and what it means for auto manufacturing.

The Role of V2X Communication

Automotive communication systems date back nearly half a century as manufacturers started designing systems to let vehicles communicate with each other in the 1970s — a concept known as vehicle-to-vehicle (V2V). V2V is still evolving, with Volvo and FedEx experimenting with automated platooning in Europe and pairing groups of trucks to follow each other on the highway.

Other types of vehicular communication include:

V2N will be critical as researchers continue improving 5G. With this system, cars will send information across networks through LTE and 5G. Experts say about 90% of American mobile connections by 2030 will be through 5G.

V2X in Auto Manufacturing

V2X is a critical technology because it combines all types of vehicular communication into one system. With this advanced mechanism, cars will be more intelligent than ever and could establish themselves as better drivers than humans. Auto manufacturers are trying to accomplish this feat with self-driving vehicles, but the industry hasn’t reached fully autonomous operations yet.

Improving V2X is essential in the race for self-driving vehicles, as this technology lets cars see and understand the world around them. An autonomous car or truck must be able to react quickly to traffic jams, emergency vehicles passing, animals crossing the road and other sudden events. Vehicles could work together and make the streets safer, thus creating a safer environment for autonomous machines.

V2X Applications

V2X offers opportunities to integrate all these technologies into one machine. This vehicular communication system exists in limited numbers currently but could soon make its way into more automobiles.

More recently, Toyota successfully tested its V2X technology in collaboration with Orange. The automaker equipped a vehicle with V2X capabilities and credited 5G and edge computing for its test track accomplishments. V2X technology warned drivers of emergency vehicles, helped them avoid collisions and accurately positioned the car.

What Are the Manufacturing Implications of V2X Communication?

V2X presents an incredible opportunity in the automotive industry to make cars smarter. What does this technology mean for manufacturing? Here are four implications to see as this concept evolves into the mainstream.

Advancing Technologies

Incorporating V2X in all auto manufacturing would make car assembly more advanced due to the AI and ML necessary for building. While some vehicles are simplistic with minimal technology features, these machines require onboard units and other devices to meet V2X’s needs. This change will require employees to understand the technology and how to include it inside the vehicles.

Standardization Needs

Automakers use vehicular communication technology like V2V, but these concepts only work with machines from the same manufacturer. For V2X’s success, auto manufacturers must standardize this technology so cars can connect seamlessly despite the logo on the front. Collaboration must also include semi-chip manufacturers, software developers and other professionals involved in advanced automotive technology.

Cybersecurity Risks

Integrating technology comes with cybersecurity risks, so automakers must ensure their V2X technology has robust security features to protect drivers. Otherwise, operators risk crashes, theft and other unwanted outcomes. One way to safeguard V2X-integrated vehicles is implementing security requirements with third parties to minimize the risk of data breaches.

Supply Chain Visibility

V2X technology can help auto manufacturers with their supply chain visibility — a critical component considering the modern economic climate. With advanced communication devices, automakers can help fleet owners with logistics management and increase transparency with suppliers. For instance, V2X’s enhanced route optimization can reduce lead time for parts, making manufacturing more efficient.

What Advantages Does V2X Communication Bring?

V2X communication is beneficial because it lets the auto industry take another step toward autonomous vehicles. What other advantages does this sector reap? Here are a few positive takeaways from V2X technology.

Driver Safety

With V2X communication, car operators can feel safer on the road. Vehicles communicate with each other to know when hazards lie ahead on the road or changing weather conditions. This benefit is even more pronounced with long-haul trucks, considering their role on America’s highways.

V2X technology in semi-trucks would let logistics professionals use autonomous trucks and reduce accidents and losses. Experts say driverless trucks perform up to 30% better than those with operators, so V2X would go a long way in promoting safety.

Environmental Benefits

Advancing vehicular communication technology also benefits the environment by cutting emissions. The transportation sector is responsible for 29% of all emissions, so reducing this output is essential. V2X can help the environment by mitigating traffic congestion, thus reducing idle time and wasted fuel in cars.

Smart City Integration

Rising urban populations mean cities will need to manage their energy grids better. V2X technology lets vehicles communicate charging needs and reduce strain on the grid. For instance, EVs could select optimal charging times — such as off-peak hours — to help the city’s energy grid and optimize efficiency.

Using V2X Communication for an Autonomous Future

Research on autonomous vehicles has surged as automakers race to be the first to debut fully self-driving cars. Reaching this level of driverless operations requires V2X devices that combine the best aspects of vehicular communication technology. These advanced mechanisms have implications for manufacturers and benefits for drivers, so the future has a lot of potential for this corner of the automotive industry.

This article is written by Jack Shaw. Jack is a seasoned automotive industry writer with over six years of experience. As the senior writer for Modded, he combines his passion for vehicles, manufacturing and technology with his expertise to deliver engaging content that resonates with enthusiasts worldwide.

Auto Parts Supplier Revs Up Its Production Process {case study}

Back to top ↑

 

Since the industrial revolution, every technological advancement has been viewed through the lens of its effect on jobs. Will I be obsolete? Can a machine do my job better than I can? Are the bots coming for me? If my skills are rendered obsolete, what will I do?

The plain truth is, sometimes machines can do the job better, faster or more efficiently than a human can. Think of the advent of the sewing machine. Even your grandmother’s old Singer model is a whole lot faster, more precise and efficient than she is working with a needle and thread. The art and craft of sewing isn’t lost or obsolete, but for sheer volume and exact replication, you can’t beat the machines.

What’s happening now with artificial intelligence (AI) in manufacturing is a little bit like that. People on all levels of the manufacturing chain want to know if AI is taking over.

The answer is no. Don’t think of it as a takeover. Think of it as more of a transformation. It’s already happening, and it’s not all bad.

AI’s current impact on manufacturing

Artificial intelligence is seeping into the manufacturing workplace in a couple of important ways.

Automation: Much like the sewing machine and indeed all of the industrial revolution, AI has the power to automate repetitive tasks previously done by humans. Operating machinery, tasks on the assembly line, even inspecting products for defects – all of these things are increasingly being automated.

Efficiency: AI can help us optimize processes and procedures, leading to greater efficiency on the line and as a whole.

New job creation. Yes, you read that right. Whereas AI may reduce the amount of jobs focused on repetitive tasks, it is also creating jobs that we haven’t seen before in the manufacturing realm, including specialized programmers, engineers, and technicians. It means companies will need people with different skill sets, and the savvy employers will dig in and train the people they already have to take on these new roles.

Predictive analytics

At USC Consulting Group, we’ve already been using AI with some of our manufacturing clients, specifically in the area of predictive analytics. We spell it all out in our eBook, “AI and Machine Learning: Predicting the Future Through Data Analytics,” but here is the gist of it in a nutshell.

By now, we all know what AI is — computer systems that perform intelligent tasks, like reasoning, learning, problem solving, decision making, and natural language processing, among others.

Machine learning is a subset of AI. It is, technically, a set of algorithms that can learn from data. Instead of having to be programmed, the computer learns on its own based on data.

Predictive analytics is one output of machine learning. It is the ability to forecast future outcomes based on data. It’s like having a crystal ball that’s informed by vast amounts of complex algorithms and data.

You’re already familiar with predictive analytics but may not know it. You know how Amazon suggests an item for you to buy based on past purchases, or Netflix queues up new shows based on what you’ve already watched? That’s predictive analytics in action.

Much like Netflix’s use of predictive analytics created a seismic shift in consumer expectations, this technology also has the potential to transform operating procedures and processes for many industries.

The benefits of using AI in predictive analytics are many, including:

Bottom line: AI needs us

AI is a powerful tool we’ve used at USCCG to help our clients achieve greater efficiency, productivity, and profits.

But here’s the thing about that. It’s a tool. And it’s only as good as the data we supply. Any variation, and there can be skewed results.

As we all know, life is not a data set. Variation is happening all around us, all the time, even in projects where we need great precision.

That’s why the bots are never going to replace humans. They need us as much as we need them. At USCCG, we have more than 50 years of experience making process improvements, finding hidden opportunities for efficiency, creating leaner systems and helping companies thrive. For the next 50, AI will be one tool we use to help achieve that.

Read more about this innovative technology, including a specific case study about how AI works in practice, in our eBook, “AI and Machine Learning: Predicting the Future Through Data Analytics.”

AI and Machine Learning - Predicting the Future Through Data Analytics eBook

Back to top ↑

 

The automotive industry is driving automation by having the largest number of robots working in factories around the world — operational stock hit a new record of about one million units, according to the International Federation of Robotics (IFR). With the prevalence of automation rising in the automotive industry, the benefits associated with its use in manufacturing cannot be understated. With advantages that work to bring productivity and efficiency all around, advancements in technology such as the integration of artificial intelligence underline the many innovative applications to come.

Exploring the current advantages of automation

“The automotive industry effectively invented automated manufacturing,” notes Marina Bill, the President of the IFR. “Today, robots are playing a vital role in enabling this industry’s transition from combustion engines to electric power. Robotic automation helps car manufacturers manage the wholesale changes to long-established manufacturing methods and technologies.” The IFR goes on to highlight the recent density of robots in the automotive industry — in the Republic of Korea, 2,867 industrial robots per 10,000 employees were in operation in 2021, while Germany had 1,500 units followed by the United States with 1,457 units.

Automation plays a variety of roles in automotive manufacturing, including taking on tasks such as screw driving, windshield installation, and wheel mounting. Automate highlights one example of a valuable role that automation plays in the manufacturing process, via an automated vehicle floor plug insertion system developed by FANUC for General Motors. As a result, the system effectively helps relieve workers from “the ergonomic strain of the manual process and improves production time.” Apart from assembly, Robotics and Automation News notes additional uses for automation in manufacturing include car painting, welding, polishing and material removal, and quality inspection. Regarding the benefits, automation in automotive manufacturing is known to have a wide variety of advantages that heighten productivity in immense ways — including lowering costs, improving accuracy and safety, and amping up efficiency.

Increasing automation highlights a productive future

According to CBT News, automakers are “likely to introduce more robots and other forms of automation over time.” Currently, CBT notes that many robots on production lines are called ‘cobots,’ as they work alongside workers in order to complete tasks that are physically demanding or more challenging to do — Ford, for example, has “at least 100 of these cobots across two dozen of their plants around the world.” Automakers are already planning for increased automation in the future in order to achieve various goals. Tesla is a pioneer regarding factory automation and robots; Elon Musk, for example, has said that introducing more automated equipment at Tesla as part of a goal to cut the costs of making future models by 50%, according to CBT News.

To further underline the presence of automation in auto manufacturing, a 2021 article from The Korea Economic Daily Global Edition highlights the use of robots and artificial intelligence (AI) by Kia Corp., South Korea’s second-largest automaker. According to the article, the company had released a video “showing a highly automated production line of the all-electric mid-size crossover utility vehicle (CUV) at a smart factory powered by artificial intelligence and robot technology.” Crossovers have risen in popularity in the US, with the vehicle featuring an SUV-style body based on a car (rather than a truck platform), therefore using unit-body construction. Today’s crossovers offer a variety of features, with top-rated crossovers offering those such as a spacious interior and a smooth engine.

Innovation foreshadows advancements to come

In addition to simply expanding automation efforts throughout auto manufacturing, ‘smart manufacturing’ employs technology in addition to automation. Also called Industry 4.0, RT Insights notes that data-driven decision-making and predictive maintenance are just the beginning of the advantages associated with smart manufacturing, with benefits extending to areas such as energy efficiency and supply chain optimization. “The resulting factors of having a smart manufacturing set-up are efficiency, production optimization, trackability, quick turnaround during downtime, safer working conditions, and responsible manufacturing,” notes Mobility Outlook.

AI and machine learning (ML) are both components that are driving the future of smart manufacturing, with Mobility Outlook explaining that AI systems analyze data sets and historical records of Internet of Things (IoT) devices. As a result, AI can identify patterns and trends which would otherwise go unnoticed by workers. ML algorithms, on the other hand, can “learn from data, make predictions, and make suggestions to improve manufacturing processes.” Predictive maintenance can also make a major difference in the future of automotive manufacturing, with the analysis of data allowing for minimized repair costs and proactive maintenance. Furthermore, Mobility Outlook highlights the value of quality control systems powered by AI — with this technology, defects can be detected in real-time, allowing for waste reduction and improved product quality across the board.

Automation brings a variety of benefits to automotive manufacturing. While automakers are already making use of the technology, technological advancements like AI are driving the future of ‘smart manufacturing,’ effectively foreshadowing a range of advantages to come.

*This article is written by Lottie Westfield. Lottie spent more than a decade working in quality management in the automotive sector before taking a step back to start a family. She has since reconnected with her first love of writing and enjoys contributing to a range of publications, both print and online.

Back to top ↑

 

Mining companies know all too well how expensive and dangerous the industry can be, and the demand for safer and more efficient training and procedures is increasing year on year.

The good news is that technology is keeping up with this demand and mining companies are starting to welcome and integrate innovative tech into their procedures.

From virtual reality training sessions to 3D mapping and printing, mining technology is helping streamline complex processes and tasks while reducing safety risks and costs.

In this article, we’re going to look at 7 mining technology innovations that are driving the mining industry forward and the benefits they bring.

1. Mining Drones

Drones have been around for the best part of a decade now and have become popular pieces of mining technology to access hard-to-reach areas and sites.

Drones are transforming the way operators map and survey mining sites. Surveying and mapping sites on foot are often expensive and time-consuming, but drones can relay geophysical imagery and data to surveyors quickly and efficiently without putting anyone’s safety at risk.

Another obvious benefit of drones is the time saved surveying sites and carrying out inspections. Operators are able to use drones to conduct visual inspections of sites and equipment as well as provide surveying and mapping data.

Companies like Exyn Technologies use drones to map out a 3-dimensional landscape of underground mines without compromising employee safety. These drones deliver hyper-accurate, survey-grade 3D maps in real-time. Plus, they’re able to navigate mines with little to no light with ease.

To learn more about Exyn technology and how it compares to more traditional methods, check out our study of Mining’s Top Innovations.

2. Virtual Reality

One of the best implementations of VR in the mining industry is how it’s being used to train employees. Mining companies can now use VR to provide immersive and realistic training simulations to allow employees to practice and navigate complex tasks in a safe and controlled environment.

VR also allows miners to virtually explore mining sites without needing to physically be there. Again, this negates the safety issues concerning visiting dangerous mining sites, but also saves money on travel expenses and transporting cumbersome equipment around the world.

Employees can practice using hyper-realistic machinery through VR, allowing them to experience operating heavy and often complex machinery off-site. This means trainees can learn and make mistakes on the job without severe consequences.

3. 3D Printing

3D printing looks to have a bright future in the mining industry. The ability to print and replicate complex and often expensive mining equipment can save companies a small fortune.

For example, if a piece of equipment becomes damaged during use, companies can use 3D printing to replace this equipment quickly and with incredible accuracy. Sourcing mining equipment is often costly and can take time to deliver specific equipment to mining sites. With 3D printing, both of these issues are negated.

While 3D printing is seeing a steady introduction to the mining industry, the potential it brings could be game-changing. Being able to instantly find, print and install specific tools or parts onsite to damaged machinery can reduce lead times and negate the need to transport expensive equipment to remote sites.

Plus, you don’t need a warehouse to store these parts – as every part can be stored digitally!

4. 3D Mapping

3D mapping is a form of mining technology that provides extremely accurate and detailed digital representations of mining sites.

For example, 3D mapping tools can highlight and pinpoint important areas for excavation, without wasting time and valuable resources. Additionally, it isn’t limited to just mining sites – 3D mapping can also be used to map quarries, waste deposits and transportation routes.

According to the statistics, the global 3D market is expected to grow from $3.8 billion in 2020 to $7.6 billion by 2025.

5. Artificial Intelligence

It would be an understatement to say that AI dominated the technology headlines of 2023. The introduction of ChatGPT, Midjourney and BingChat had (and continues to have) a massive impact on operational processes in almost every industry.

In the mining industry, AI is leveraging smart data and machine learning. Not only does this mean safer training and better mining processes, but it cuts the time to perform these tasks in half. This enables onsite engineers to make decisions faster and with more accuracy.

For example, AI is helping mining companies locate and extract valuable minerals with precision. Additionally, through advanced algorithms and data analysis, AI systems can identify optimal mining sites, predict potential resource deposits, and even guide exploration efforts with exceptional efficiency.

We’re already seeing how AI mining technology is aiding autonomous equipment like self-driving vehicles for tunneling excursions and optimizing drilling systems, and we’ll likely see more processes utilizing AI going into the future.

6. Automation

Automation is becoming increasingly popular in the mining world. Truckless conveyor-belt ore transport systems, subterranean electric vehicles and drones are some of the core automation shifts we’re seeing.

One of the biggest benefits of automation is that it allows mining companies to work around the clock without having to be physically present. By automating processes like ore delivery and transport, site monitoring and drilling and ventilation systems, miners do not have to jeopardize their health and safety by venturing into mines and handling hazardous materials and minerals.

Instead, miners can be trained on how to operate heavy machinery remotely from a control center above ground, providing a safer and more comfortable working environment.

Yes, time and resources will need to be invested in training miners on how to use this mining technology. However, the benefits far outweigh the cons. Miners face fewer health and safety risks, speed and efficiency will likely increase and in the long term the industry will experience significant cost savings.

7. Digital Twinning

Digital twinning allows mining companies to create a digital replica of their entire mining ecosystem. This includes mining equipment, geological formations and other relevant objects or assets.

By integrating data from sensors, IoT devices, and other sources, digital twinning provides a dynamic and detailed simulation that mirrors the physical reality of the mining site.

The main aim of digital twinning in the mining industry is to improve decision-making and operational efficiency. Digital twinning also allows miners to simulate various conditions and assess the impact of different variables on operations. This approach means fewer safety risks for employees.

Digital twinning is changing how mining companies do things. It lets them make a digital copy of their entire mining setup, including their equipment, geology, and processes, in an instance.

In essence, digital twinning is making mining operations more efficient, sustainable, and competitive.

Conclusion

The mining industry has been calling out for more innovative and efficient ways to streamline their processes and improve the safety conditions of their employees.

The mining technology at their disposal today is revolutionizing traditional mining processes and more companies will inevitably invest in this new technology.

Improved productivity, enhanced safety and substantial cost savings are just a few of the benefits technology brings to the mining industry. In the next few years, mining companies will need to adopt this technology into their processes to stay competitive and meet the growing demands for sustainability and efficiency.

Embracing these technological advancements is not just a choice; it’s a necessity for the mining industry to thrive in the evolving landscape.

*This article is written by Sophie Bishop. Sophie is an experienced freelance writer with a passion for sharing insights and her experience within the health and safety sector. Sophie aims to spread awareness through her writing around issues to do with healthcare, wellbeing and sustainability within the industry and is looking to connect with an engaged audience. Contact Sophie via her website: https://sophiebishop.uk/.

Back to top ↑

 

Studies have shown that over 40% of workers across various industries spend a significant portion of their workweek on repetitive manual tasks. In the manufacturing sector, these tasks often involve data collection and manual data entry, which many consider to be inefficient given the availability of advanced automation software in today’s market.

Innovative automation programs are designed to automatically collect, upload, or synchronize data into a system of record. This automation can help eliminate production bottlenecks and streamline manufacturing processes, ultimately improving output. Moreover, automation can significantly reduce the risk of human error, which can lead to injuries. In fact, a majority of workers (nearly 60%) believe that they could save six or more hours per week if the repetitive aspects of their jobs were automated.

Automation is not limited to the field personnel, as managers are also looking to streamline their own tasks. A renowned technological research and consulting firm predicts that by 2024, 69% of day-to-day managerial work will be fully automated. Examples of automatable managerial tasks include approvals, sign-offs, status updates, and confirmation requests. Increased efficiency in these operations can free up time for employees at all levels to contribute more strategically to the success of a business.

In addition to automation, cutting-edge robotic technology is also being utilized in many manufacturing organizations. Programmed robots or robot-controlled machines that use artificial intelligence (AI) can enhance a company’s assembly, material handling, and processing capabilities. Robots excel in predictable environments and can handle physically demanding or monotonous tasks that may negatively impact employee well-being or morale. This results in increased productivity and reduced labor costs.

Another type of robot gaining popularity is the collaborative robot, or cobot, which is specifically designed for direct human-robot interaction. Cobots are relatively new but are projected to have exponential growth in the market, with an estimated worth of nearly $2 billion by 2026, up from $590.5 million in 2020. Industry experts predict that by 2025, 34% of industrial robots sold will be cobots. Cobots are cost-effective, safe, and flexible, making them an ideal tool for small and mid-sized manufacturers to modernize their operations, reduce redundant tasks, improve productivity, and achieve peak performance.

To learn more about the impact of repetitive tasks in manufacturing and how technology can counter them, please refer to the infographic below:

Repetitive Tasks in Manufacturing from Acieta, a manufacturing robotic company

 

Back to top ↑

 

Manufacturers have had an uneasy past two years. Disruptions early in the pandemic nearly brought production to a halt in some areas, and now, supply chain shortages plague the industry.

Building materials have seen some of the most dramatic shortages, with 94% of surveyed builders struggling to find framing lumber. Electronics manufacturers and those relying on them have struggled, too. The automotive industry stands to lose $61 billion this year due to semiconductor shortages.

Other materials and parts in short supply include palm oil, plastics, corn, steel, and chlorine.

The Causes Behind Manufacturing Supply Shortages

There are many factors behind these shortages, most of them sprouting from the pandemic. Economic downturns and worksite restrictions have stopped or slowed many processes like farming, mining, and parts production globally. Even as these obstacles fade, these producers of materials and parts find themselves with considerable backlogs, leading to ongoing shortages.

A surge in demand has compounded these supply issues. General manufacturing demand was already increasing, with U.K. consumers alone spending more than $1.6 billion online weekly in 2019. E-commerce skyrocketed further amid the pandemic, and on the commercial side, many manufacturers rushed to meet previous production levels, outpacing their still-struggling suppliers.

International travel restrictions have also made shipping slower and more expensive, exacerbating the crisis.

Strategies for Mitigating Supply Issues

While there is no silver bullet for these supply shortages in manufacturing, several steps can mitigate their impact. Manufacturers can also take this opportunity to prepare against future disruptions, avoiding similar situations. Here are three leading strategies for navigating these supply issues.

1. Improving Visibility

One of the most crucial changes to make is to increase visibility across the supply chain. Internet of things (IoT) technology and data analytics programs can give manufacturers more insight into stock levels and developing situations. They can then predict shortages and take steps early to account for them.

Real-time visibility can also help track shipments to give customers a better idea of when they can expect their end products. Over time, this data can inform more accurate predictions and reveal needed workflow changes. Manufacturers can then become more resilient against supply chain issues.

2. Diversifying Sources

In manufacturing, many facilities tend to source from a single supplier. While this minimizes costs, it also intensifies shortages when disruptions arise. Manufacturers can lessen the impact of slowdowns and other unexpected issues by diversifying their sources.

Much like how Amazon uses artificial intelligence (AI) to keep merchandise close to consumers, manufacturers can analyze data to find ideal nearby sources. Domestic or near-short suppliers will produce fewer disruptions in a crisis as there’s less distance and fewer regulations involved. Using multiple suppliers will further reduce shortages by removing dependencies.

3. Turning to Alternatives

Some manufacturers have found relative success in using alternative materials to account for shortages. For example, some construction material companies have switched to unconventional insulation materials in the face of petroleum shortages. Manufacturers may be able to adjust processes to use novel or less-common materials to maintain production.

If facilities take this route, being transparent with customers is crucial. End products may have different qualities or incur higher prices with new materials, so manufacturers must be upfront about these changes. They may cause initial disruptions but can mitigate persistent issues with conventional parts.

Manufacturing Must Adapt Amid Widespread Shortages

Given the prevalence and severity of these shortages, they won’t likely go away soon. It will take time for production to fulfill backlogs and meet demand. On the positive side, this increased demand indicates healthy industry growth, but manufacturers must prevent similar crises in the future.

Since these shortages are multifaceted issues, no one solution will fix them. Adopting a multi-step approach, including implementing new technologies for visibility and adjusting sourcing methods, is essential. The industry faces significant obstacles right now, but these will inspire positive change for the future.

*This article is written by Devin Partida. Devin is a tech writer with an interest in IIoT and manufacturing. She is also the Editor-in-Chief of ReHack.com.

Need more horsepower for your change management project

Back to top ↑

 

When the general public hears the word “warehouse,” they most likely envision a rather low-tech environment. After all, a warehouse is but a large building filled with shelves and boxes, right? That may have been true in the past, but today these facilities are on the cutting edge of technology in a big way.

The demands of e-commerce and the impact it has had on traditional retail have made speed and efficiency absolutely essential. Warehousing is a critical link in the supply chain, and as such it needs to adopt every technological advantage to keep up with consumers’ expectations.

What Warehousing Looks Like Today

Far from the dusty, quiet spaces many people might imagine, the warehouses of today are extremely high-tech environments. They need to be, with thousands of SKUs on the shelves and just as many orders pouring in every day. The technology these operations employ take many forms, from handheld scanners to robotic arms to cloud-based software platforms. What they all have in common, however, is a focus on improving the flow of orders and goods through the supply chain.

For instance, one of the most conspicuous additions to these facilities in recent years is the autonomous vehicle. Driven automatically by computers, these motorized carts and forklifts are now responsible for much of the heavy lifting in many warehouses. Because they don’t require operators and can work around the clock, they have been a crucial factor in improving productivity and efficiency in many buildings.

Another recent development is the introduction of wearable devices that keep personnel connected to a centralized system at all times. One primary example is voice picking, which directs workers to items to be picked through computer-generated verbal instructions delivered over a headset. This results in more efficiency, less paperwork and up-to-the-minute information. Plus, it keeps workers’ hands free to do their jobs more effectively.

Envisioning the Future of Warehouses

As the speed of commerce continues to increase and consumers rely on more online shopping, the need for high-tech solutions in the warehouse is only increasing. Even if most facilities don’t use artificial intelligence or handheld devices right now, that doesn’t mean they won’t.

To learn more about common technologies that are transforming the warehousing industry, take a look at the accompanying infographic. It details some of the most popular and powerful devices and concepts that are expected to have a significant impact now and in the near future.

The Warehouse of the Future infographic

The Warehouse of the Future from The Numina Group

The future is now in many cases, but if your organization needs a helping hand to affect positive change in your operations please give us a call. We can improve your process efficiency, inventory management, and guide your team into the future.

Looking to optimize your supply chain

Back to top ↑

 

The last couple of decades have seen some significant changes affecting the logistics industry, and the supply chain as a whole. New regulations to working practices have forced fleets to more carefully monitor drivers, and make adjustments to ensure efficiency is maintained. The driver shortage also remains a problem, with some agencies predicting that the deficit could rise to 160,000 within the next decade.

Rising alongside these challenges, though, are technological advances. Some of them have the potential to help solve the prevalent issues of our industry, others could transform the shipping business as we know it. Technology continues to develop at a rapid rate, and advances such as artificial intelligence (AI) and autonomous vehicles are already starting to make an impact in the logistics industry.

We’re going to take a look at areas in which AI and autonomy both have the potential to alter the way the logistics industry does business, and how those we’ve already begun to embrace are developing. How might these affect the roles of workers in the sector, and what do we need to prepare for?

Fleet Management

Freight transportation is one of the most important industries to the health of the US economy. It not only provides a vital lifeline of essential products across the country, but it also gives us a valuable insight into consumer behavior and market fluctuations. When freight providers use tech tools to make their operations more efficient, there’s an opportunity to keep this indispensable economic resource serving the nation effectively.

Understanding the Importance of Strategic Sourcing eBook

For many companies, these operations take the form of ground freight — the use of fleets of trucks to quickly and cheaply deliver goods. In this sector, fleet management is an essential tool, which has also become one of the early adopters of AI software. With multiple mobile assets and constantly evolving variables such as road conditions and weather patterns, AI software does the grunt work of receiving and analyzing data. This software also factors in information from maps and vehicle service history, allowing for predictive maintenance. As a result, managers receive real-time predictions that allow them to make efficient advanced plans, and adjust them swiftly when conditions change.

One of the positives of utilizing AI in fleet management is its ability to keep learning. Collecting data from devices such as onboard vehicle diagnostics, GPS, and camera footage, the software is being fed evolving information that allows it to improve the predictions it makes. AI is reliant upon the quality of data and engaging with other tools that allow fleets to build better industry networks, and sharing important operational information can be key in giving AI platforms the information they need to bolster the entire logistics industry.

Safety Driven by Technology

Safety continues to be a key concern across the fleet industry. In recent years we’ve seen regulations come into effect that restrict the hours that drivers can be on the road, and technology — in the form of electronic logging devices that track drivers movements — is a mandatory feature in remaining DOT compliant. However, fleets have begun to look beyond these basic requirements to discover new ways for AI and autonomous tech to keep everyone safe.

Fully autonomous trucking is neither practical nor safe just yet and is unlikely to make an appearance for several years to come. However, some limited autonomy has found its way into trucks to improve safety. Adaptive cruise control is a prominent example of level 2 automation. It uses a combination of radar and a camera to detect the distance of objects in front of the truck, regulating the speed of the vehicle to reduce the potential for emergency braking.

These small, incremental improvements serve to gradually build confidence in the industry and the public. Legislators have started to approve certain aspects of autonomy, and as a result, we’ve started to see a ramping up of testing. Volvo and FedEx have recently trialed automated platooning in Europe, using vehicle to vehicle (V2V) communications systems and advanced driver assistance (ADA) to allow multiple trucks to maintain close distances behind one another on highways safely.

Logistics industry technology continues to improve trucking advancements.

Staff Supported, Not Replaced

One of the key concerns surrounding automated systems such as self-driving vehicles and AI is their effect on employment. However, it’s been clear from the way in which this technology has been used and trialed in the logistics industry so far that the preference is to support workers rather than replace them.

Recently, UPS and Waymo teamed up to pilot autonomous package pickup in the Phoenix Metro area. This kind of short distance usage, to fill in the gaps for efficiency, could be an indicator of how autonomous trucking is likely to advance. Last-mile delivery is one of the areas in which there is a deficit of drivers, and there are expectations that this could be the key focus for autonomy, rather than long-distance driving.

It’s important to note that trials for full autonomy have required the presence of a human expert on board or in a supervisory role. This could also be an indicator of a change of career path for those in the trucking industry. Rather than removing jobs from the freight sector, automation could see a range of new skilled positions being introduced. Drivers could see their roles expanding to become on the road automation technicians, too. Though fleets may also need to start planning for the raise in salary level such high skilled workers will be able to command.

Progressing Forward

While we are not yet in a fully autonomous, AI-controlled world, elements of this technology have started to appear across the logistics industry. The slow and steady approach that the sector is taking allows us to assess where the challenges might lay, and make sensible adjustments accordingly. Workers and leaders alike need to watch how these advances are progressing, and plan to make changes in their investments and skill sets accordingly.

This article is written by guest author Beau Peters. View more of Beau’s articles here.

 

Looking to optimize your supply chain

 

Back to top ↑

 

The 2010s are now a memory. Every decade has its fair share of ups and downs, but by most measures, this past decade was a good one for much of the country.

Granted, due to the Great Recession, the U.S. economy started out in a bit of a rough patch. However, thanks in part to regulatory changes and good old fashioned entrepreneurialism, the unemployment rate has reached record lows nationwide and extreme poverty globally is now in the single digits (8.6% from 18.2%, according to World Bank data).

“Operational excellence is the unyielding pursuit of greatness.”

There were many notable strides in the 2010s aside from sheer job growth. Such improvements were largely due to the role of operational excellence. Whether in terms of productivity, creativity or ingenuity, operational excellence is the unyielding pursuit of greatness, the constant and consistent refining of current processes in order to achieve a better outcome. According to polling conducted by the Institute for Operational Excellence, more than 70% of businesses professionals say OpEx is instilled in the very fabric of their company’s culture. Whether it’s business transformation, lean six sigma, process improvements or business process management, these methods are all designed to help businesses reach a little farther and dig a little deeper in terms of becoming better than they were yesterday, a month, or a year ago.

There are many ways to examine the OpEx lifecycle from 2010 to today, but perhaps the most salient examples are technological development, process management and ideologies, meaning the beliefs that help inform businesses’ strategy and understanding of what is the most important aspect of their operations. Here are a few examples from each category that show how the role of operational excellence has evolved over time.

Technology: Automated intelligence

Automation has changed the world in an extraordinary number of ways. From ubiquitous handheld technology, fast-food kiosks in restaurants and robotic installations in factory settings, automation today is everywhere. In the early 2000s, the share of new robot installations in hi-tech manufacturing rose 21% to a total of 21,000 worldwide, according to Oxford Economics. But by the mid-2010s, they grew an additional 31% to 91,000 in 2016.

What accounts for the surge? For starters, automation-related processes are not only better by today, but cheaper. As a result, more employees are working alongside robotics in order to manufacture and deliver products quicker and more efficiently. Much of this is attributable to growth and development in technological improvements in things like machine learning.

Karen Hao of MIT Technology Review wrote in 2018 that were it not for machine learning, many of the artificial intelligence advancements — such as viewing recommendations on Netflix or “fill in the blank” search suggestions on Google — would have stalled.

Technology and automated intelligence has contributed to the role of operational excellence

“Machine learning has enabled near-human and even superhuman abilities in transcribing speech from voice, recognizing emotions from audio or video recordings, as well as forging handwriting or video,” Hao explained, as quoted by Popular Mechanics.

While some presidential hopefuls and economists warn of significant job losses posed by automation, only 27% of respondents are worried about such a scenario affecting them, according to polling conducted by CNBC and Survey Monkey. This may be a function of  employers retraining employees and repositioning them in roles where their skills can be better leveraged and in a better position for the company to achieve operational excellence.

Processes: Change management

In order to achieve results and get to a better place, change may be necessary. By its very nature, change is difficult, but in order to move forward, develop and learn from previous mistakes, structural or process-related changes may be required.

The roots of change management trace back to the early-to-mid 20th century from thought pioneers like Arnold van Gennep and  Kurt Lewin. The last 10 years or so has resulted in change management taking on a life of its own, as not only have most businesses heard of the term, they’ve refined the process so whole-scale changes are less drastic.

“Change management is best accomplished through evolutionary changes.”

As noted by Oracle Technical Program Manager Burhan Syed, this has come from a greater focus on implementing evolutionary changes rather than revolutionary, using a more methodical, incremental approach versus those that are all at once. Today, change management is a process-related strategy as well as a profession, as companies hire individuals or operations management consultants to lead these sweeping efforts. Regardless of who pilots them, leadership is key.

“Leaders need to understand that their management styles must be able to adapt to the nuances of championing organizational change,” Syed wrote.

Ideology: Customer experience

While many would argue that the customer experience is every bit as important today as it was in 2010, few can deny the extent to which its become a singular focus. This is largely due to a greater number of companies vying over a smaller pool of consumers, so they must distinguish themselves to earn their loyalty. When it comes to measuring the success of improvements efforts, the third most common response among business owners point to is customer satisfaction, the Institute for Operational Excellence found.

Connie Moore of the Digital Clarity Group points to organizational change management, innovation, “outside the box” thinking and analytics as some of the key drivers to improving and refining the customer experience on an ongoing basis.

What will be the key takeaways in the 2020s and beyond? Time will tell, but you can make the decade a successful one by working with USC Consulting Group. From asset utilization to productivity improvements, sales effectiveness to cycle time reduction, we can help you achieve operational excellence so your greatest challenges in 2019 become your biggest strengths in the days ahead. Contact us to learn more.

 

Looking to empower your operational performance

 

Back to top ↑