Tag Archives: Artificial Intelligence

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:

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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.

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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 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.

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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.

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.

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.

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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).

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.

“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.

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.

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