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How AI and the Augmented Connected Workforce is Revolutionizing the Packaging Industry

Join Chris Kuntz for an interview Packaging Insights on how AI and connected worker technology can help the packaging industry overcome the skilled labor crisis.

The packaging industry has been hit by the low availability of skilled workers, but for Chris Kuntz, VP of Strategic Operations at Augmentir, AI systems offer the solution. In this interview with Joshua Poole from Packaging Insights, Chris explores how AI and the Augmented Connected Workforce could revolutionize the packaging industry and how Augmentir’s AI-powered connected worker solution supports optimal efficiencies in manufacturing. He also discusses the importance of effective regulatory frameworks for AI.

This transcript has been edited for clarity and length. View the original video interview on the Packaging Insights website here.

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packaging industry connected workforce

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Joshua Poole: Hello, everyone. My name is Joshua Poole, and I am the editorial team leader at CNS Media, the publisher of Packaging Insights. I am very pleased to be joined today by Chris Kuntz, who is the Vice President of Strategy at Augmentir, and who is here to talk about the benefits of AI in relation to the packaging industry.

So welcome to you, Chris.

Chris Kuntz: Thank you very much, and thanks for having me, Joshua.

Joshua Poole: So, Chris, AI systems are expected to really transform the wider society but in relation to the packaging industry, to what extent could they revolutionize operations there?

Chris Kuntz: The reality is, to a huge extent. The impact centers around the manufacturing workforce – the people that are part of manufacturing. Historically, the application of AI, artificial intelligence, and machine learning, in manufacturing anyway, has focused on automating repetitive lower-level processes, that replace humans in the factory. Today, what we need to think about, and what we focus on here at Augmentir, is how we can use AI to augment the human workforce. And so, AI, again, used throughout the industry, its served great application from a predictive maintenance, machine failure standpoint, energy efficiency – things like resource utilization and even supply chain visibility and quality control.

And those applications of AI in manufacturing will continue to provide value. But the reality is people are still needed in paper mills, on the factory floor in the areas of safety, quality, and maintenance. There are jobs that just require that humans are there. And that’s not going away any time soon. But what we are faced with, and what many manufacturers are faced with, is these workforce challenges of the aging workforce, the retiring workforce going away. They’re walking out the door with a vast amount of knowledge that is essential to operate factories and plants. Pre-pandemic we had an emerging workforce coming in that maybe didn’t have the necessary skills, but today post-pandemic era, there’s a massive job shortage. There are no workers coming in, and so manufacturers are forced to look at a pool of less-skilled workers to perform tasks that they may not be initially qualified for.

So, it is not just that the skilled labor is going out, it’s just that we don’t have any skills coming in. And so, every manufacturer is faced with a massive labor shortage and as a result a massive shortage of skills required to operate successfully any given day on the shop floor. And that’s really where we think the value is going to come from an AI standpoint, and it’s kind of transformative when you look at historically the application of AI in manufacturing.

Joshua Poole: So, you mentioned the industry is really struggling to overcome the lack of a qualified workforce. How can AI overcome this problem across the industry?

Chris Kuntz: One of the great things about artificial intelligence, and our history as a company, and one of our previous companies was focused on collecting data from connected machines and then using that data and analyzing that data with AI to understand how to make those machines operate better and improve those machines.

From a human standpoint, humans have been relatively disconnected on the shop floor. They’re using paper-based checklists and SOPs and work procedures, the same sort of technology they were using 20, 30 years ago. So, they’re relatively disconnected, and we know little about how they’re operating and how they’re performing and where they need help and where they need assistance.

If we can connect those workers – and I am talking connecting with phones, tablets, wearable devices – if we can connect those workers we have a digital portal into how they’re performing, and through AI we can analyze how they’re performing and then offer them real-time guidance almost like an AI assistant that’s sitting there helping them out if they are struggling, helping them out if they need help, guidance, or support, or if there is a potential safety or security issue that they might be running into.

The same way that AI has historically been used to act on machine data to improve machine efficiency and performance, we can use the same approach for the humans in the factory.

Joshua Poole: Mm-hmm, and can you provide any examples of the ways in which your platform, Augmentir, has benefited companies looking to embrace AI to improve their operations?

Chris Kuntz: Yes, there are a few different ways. More recently we just launched our Generative AI assistant called Augie™. And what that does is that allows workers or operations managers, using natural language, to solve problems faster, assist in troubleshooting, and provide guidance when needed.

One of the first use cases is troubleshooting. This happens every day in a plant, in a paper mill, it happens every day – there’s a problem with a machine, we need to get it back up and running. Otherwise, there’s a downtime issue, which leads to production/revenue loss. And it’s not a standard procedure to fix the machine. And so there’s troubleshooting that needs to happen. This process is very collaborative. But also from a worker standpoint, they typically have to go to 5, 6, 10 different systems to try to find information or talk to different people.

And what a Generative AI assistant can do is be that digital front end to all that wealth of information and return information on, “Hey here’s the solution to this problem. It’s been solved before, it’s in this published guide, here you go.” Or, “You may want refer at this work procedure. This is something, a troubleshooting guide that could help you solve the problem.” Or, “Here’s a subject matter expert that exists” and you can remotely connect to this person who has expertise in this particular type of equipment.

And so being able to give real-time access to that individual at the time of need is critical. And I think the other big area, at least early on here, is around training.

So, if you think about the skilled labor, workforce shortage, the tenure rates in manufacturing, people are quitting faster. They’re not sticking around for 15 years, they’re sticking around for three years, maybe, possibly, at max. And so, training and learning and development, HR leaders have to think about how to change onboarding practices because it’s not practical anymore to onboard someone for six months if they’re only gonna be around for nine months.

And so the goal, with many of the organizations that we speak with, the goal is to reimagine and rethink training and move it away from the before they’re productive in the classroom to move it onto the floor. Move it into the flow of work, they call it. And so what we can do with AI there is, we don’t understand that worker or their skill level or their competency levels. And if that’s digitally tracked, we can use AI to augment those work instructions and work procedures to say, “Hey, you’re a novice. This is your first month on the job. You’re required to watch this safety video before you do this routine.” And if you’re an expert worker, maybe you wouldn’t be required to do that. Or if you were trained, but your performance is lagging vs. the benchmark, we can come – the instructions can come and be dynamically adjusted to say, “Hey, here’s some additional guidance to help you through this procedure and through this routine.”

So, it gives visibility and insight into areas. I mean, if you had three people on the shop floor, you’d probably know exactly what they were doing. But once you get some larger organizations and they have dozens of people or hundreds of people, it becomes much much harder to understand where the opportunities for improvement are. And AI has the ability to do that, certainly in the training area.

Joshua Poole: Hmm, that’s very interesting. And of course, AI is largely unregulated worldwide, which can create problems like AI washing and irresponsible use. But what do you see as the biggest concern with the proliferation of AI systems within the packaging industry?

Chris Kuntz: So, certainly there’s a lot of concerns with respect to that, and for Augmentir, our approach is we leverage a – certainly from a Generative AI standpoint, we leverage a proprietary, fit-for-purpose, pre-trained large language model that sits behind our Generative AI solution. And when you combine that with robust security and permissions that can help factory managers, operators, and ever engineers or frontline workers only have access to the information that they need, and still provide the benefits of problem-solving faster and improved collaboration.

One of the other things though that I think is really important is this concept of “verified content” – so we’ve all used ChatGPT, right? And early on, I think they had this disclaimer, ChatGPT is 90% correct, so it could return false data. That’s not just not acceptable in an industrial settting. You can’t say, “Here’s a routine to do a centerlining on a piece of equipment” and have someone stick their hand in a place and get it chopped off. You can’t be 90%, you have to be 100%.

So, we have a concept of our Generative AI system, the ability to return verified and unverified data, and then the organization can decide what they want to do with that. So, if it’s a frontline worker, maybe, if it is unverified data, it’s labeled, and you need a supervisor that has to come over if you are going to perform that routine. And then the ability to sort of take the information that comes back and categorize it in terms of verified data, unverified data, and then be able to control how you’re using that. So, it’s not the wild wild west, it’s a very controlled environment. The scope of, if you think about our, in our world, if we’re serving a manufacturing company – and Augmentir is being used for digital manufacturing in paper and packaging companies like Graphic Packaging and WestRock, and so the information that, in our scope of their world is corporate documentation, engineering documentation, operational data, work order data, people data – could be their skills matrix and training history and things like that, but it’s all contained within their enterprise. We’re not looking outside of that, it’s really a constrained data set. And that’s what feeds our large language model.

That significantly helps the application of this, there are people that are exploring using more open AI and GPT models to do this. But then you run into the problems that you said, where there’s a lot of information that both you are feeding into the AI, which could be a security risk, and then the information that you are getting back that could be a security risk.

Joshua Poole: Okay, and as a final question. What advice would you give to politicians working to establish these regulatory frameworks for AI systems?

Chris Kuntz: Great question.

You know, our point of view is we think, you know President Biden had the AI regulation executive order here in the United States back in October, we think it’s much needed on several fronts. Certainly, every company now is saying that they’re an AI company and trying to sprinkle in AI to everything they do. And some of that can be a little problematic.

But at least in the U.S. here in Biden’s AI regulation executive order, there was a lot of talk about job disruptions and putting focus on the labor and union concerns related to AI policies. I think that reinforces our use of AI as a way to augment workers. We’re not looking to replace workers and it’s addressing a huge problem. I think the Department of Labor, they’re issuing guidance to employers around AI that you can’t use it to track workers and you can’t use it to, you know there’s labor rights that exist in the world. And I think that gets back to having these AI co-pilots or Generative AI assistants that can help workers perform their jobs safely and correctly, maximizing the potential. It’s really where on-the-job learning comes into play. It’s things that were happening off the factory floor before. Now it’s squarely suited to help address some of the big manufacturing labor workforce problems that exist today. So, there’s a lot of language in that executive order around making sure that AI is used, not just responsibly, but used for purposes that are going to further the industry. And again, that’s squarely where we sit in terms of workforce development and using it to address the labor shortages from a training and support standpoint.

But, overall, I think, absolutely we embrace the regulatory – Generative AI regulation – and control aspects of this because it could become problematic if you are not doing that, for sure.

Joshua Poole: Mm-Hmm that’s very interesting. Chris, thanks for your time today.

Chris Kuntz: Yes, thank you very much. Thanks for having me.

 

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The Evolution of AI in Manufacturing

The evolution of AI in manufacturing has seen tremendous growth over the past few decades, now becoming more adaptive and collaborative, and being used to augment and directly support frontline workers.

The evolution of artificial intelligence and machine learning technologies in manufacturing has seen tremendous growth over the past few decades, with astounding leaps in technology and industry-wide transformations.

evolution of ai in manufacturing

Dating back to the 1960’s, manufacturers started using AI in robotics and basic automation. This early usage focused on automating manual, highly repetitive human tasks such as assembly, parts handling, and sorting, allowing for higher levels of production and efficiency.

Over time, this evolved with AI-enabled machine vision systems, which were used to automate visual inspections, allowing for better quality control and precision during production cycles. More recently, AI has been at the center of warehouse automation, as well as the Industrial Internet of Things (IIoT), where physical machines and equipment are embedded with sensors and other technology for the purpose of connecting and exchanging data, which is used in predictive analytics for machine health monitoring. Manufacturers can now glean valuable insights from data collected over time about optimizing their operations for maximum efficiency without sacrificing quality.

Despite the breath of applications that AI has in the industrial setting, there is a common thread across all of the above examples – AI has largely been used to automate highly repetitive or manual tasks, or perform functions designed to replace the human worker.

However, these examples laid the groundwork for the adoption of AI in manufacturing and for the use of AI technologies that augment and directly support frontline workers today.

Read below for more information on how the use of AI and GenAI is evolving in manufacturing, and being used to augment the human worker, transforming productivity and efficiency at a time when workforce optimization is needed most.

Using AI to Augment, not Replace the Workers in our Factories

Today, AI technologies in manufacturing have evolved to encompass a diverse range of applications. According to Deloitte, 86% of surveyed manufacturing executives believe that AI-based factory solutions will be the primary drivers of competitiveness in the next five years. Robotics and automation have become more adaptive and collaborative, working alongside and augmenting human workers to streamline production processes and increase efficiency – rather than simply trying to replace them.

As computing power and algorithmic capabilities improved, AI in manufacturing has become more advanced and widespread. The emergence of Industry 4.0, characterized by the convergence of digital technologies, further accelerated AI’s role in manufacturing. By leveraging tools like connected worker solutions to gather frontline data, manufacturing organizations can now capitalize on AI’s extraordinary computing power to analyze that data and derive actionable insights, improved processes, and more.

Much like the industry has learned to optimize equipment from the 1.7 Petabytes of connected machine data that is being collected yearly, we are now able to optimize frontline work processes and people from highly granular connected worker data, with one major caveat: In order to leverage this incredibly noisy data, a system has to be designed with an AI-first strategy, where the streaming and processing of this data is intrinsic to the platform – not added as an afterthought.

The potential for AI to help augment the human worker is there, but why now?

Because for today’s manufacturers, time is not on your side.

The workforce crisis in manufacturing is accelerating, and at the forefront of the minds of Operations and HR leaders. Job quitting is up, tenure rates are down, and manufacturers struggle daily to find the skilled staff necessary to meet production and quality goals. The threat is huge – with significant impacts to safety, quality, and productivity.

AI-based connected worker solutions allow industrial companies to digitize and optimize processes that support frontline workers from “hire to retire”. These solutions leverage data from your connected workforce to optimize training investments and proactively support workers on the job, across a range of manufacturing use cases.

 

paperless factory

Furthermore, solutions that leverage Generative AI and proprietary fit-for-purpose, pre-trained Large Language Models (LLMs) can enhance operational efficiency, problem-solving, and decision-making for today’s less experienced frontline industrial workers. Generative AI assistants can leverage enterprise-wide data, provides instant access to relevant information, closes skills gaps with personalized support, offers insights into standard work and skills inventory, and identifies opportunities for continuous improvement.

Augmentir’s AI-First Journey

At Augmentir, since the beginning, we pioneered an AI-first approach toward manufacturing and connected frontline worker support. 

augmentir's ai-first journey

Many manufacturing solutions incorporated AI technology as an add-on or afterthought as the technology gained more advanced capabilities and popularity. We, however, have been championing and building a suite of solutions using AI as a foundation. Our platform was designed from the bottom up with AI capabilities in mind, placing us as a leader in the connected frontline worker field. 

  • 2019 – Augmentir launched the world’s first AI-first connected platform for manufacturing work empowering frontline workers to perform their jobs with higher quality and increased productivity while driving continuous improvement across the organization. This marked the start of our AI-first journey, giving industrial organizations the ability to digitize human-centric work processes into fully augmented procedures, providing interactive guidance, on-demand training, and remote expert support to improve productivity and quality.
  • 2020 – Augmentir unveiled True Opportunity™, the first AI-based workforce metric designed to help improve operational outcomes and frontline worker productivity through our proprietary machine learning algorithms. These algorithms take in frontline worker data, then combine it with other Augmentir and enterprise data to uncover and rank the largest capturable opportunities and then predict the effort required to capture them.
  • 2021 – Building on user feedback and field data, Augmentir reveals True Opportunity 2.0™, with improved and enhanced capabilities surrounding workforce development, quantification of work processes, benchmarking, and proficiency. By Leveraging anonymized data from millions of job executions to significantly improve and expand the platform’s ability and automatically deliver in-app AI insights we were able to increase benefits and returns for Augmentir customers.
  • 2022 – Augmentir announces the release of True Productivity™ and True Performance™. True Productivity allows industrial organizations to stack rank their largest productivity opportunities across all work processes to focus continuous improvement teams at the highest ROI and True Performance determines the proficiency of every worker at every task or skill enabling truly personalized workforce development investments.
  • 2023 – Augmentir launches Augie™ – the GenAI-powered assistant for industrial work. By incorporating the foundational technology underpinning generative AI tools like ChatGPT, we enhanced our already robust offering of AI insights and analytics. Augie adds to this, improving operational efficiency and supporting today’s less experienced frontline workforce through faster problem-solving, proactive insights, and enhanced decision-making.
  • 2024 – As this year progresses, we have already continued to refine our AI-first solutions and apply user feedback and additional features to best support frontline industrial activities and workers everywhere.
  • 2025 and beyond – True Engagement™, looking forward we predict the evolution of AI in manufacturing activities will continue, progressing until we can accurately measure signals to detect the actual engagement of industrial workers and derive useful information and insights to further enhance both HR and manufacturing processes.

We are deeply involved in applying AI and emerging technologies to manufacturing activities to augment frontline workers, not replace them. Providing enhanced support, access to key knowledge (when and where it does the most good), and improving overall operational efficiency and productivity.

The Future of AI in Manufacturing – The Journey Forward

As we press onward into the future, we at Augmentir are determined to champion the application of AI and smart manufacturing to augment and enhance frontline workers and industrial processes. We will continue to evolve our application of AI and its use cases in manufacturing to help frontline teams and workforces, reinforcing our AI-first pedigree.

The addition of Augie to our existing AI-powered connected worker solution is an important step forward. Augie is a Generative AI assistant that uses enterprise-wide data, provides instant access to relevant information, closes skills gaps with personalized support, offers insights into standard work and skills inventory, and identifies opportunities for continuous improvement. Augie is a result of our dedication to empowering frontline workers, leveraging AI to support manufacturing operations, and giving manufacturing workers better tools to do their jobs safely and more efficiently.

With patented AI-driven insights that digitize and optimize manufacturing workflows, training and development, workforce allocation, and operational excellence, Augmentir is trusted by manufacturing leaders as a industrial transformation partner delivering measurable results across operations. Schedule a live demo today to learn more.

 

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AI: Revolutionizing How Humans Work in Manufacturing

AI is playing a key role in changing the manufacturing landscape, augmenting workers and empowering them with improved, optimized processes, better data, and personalized instruction.

Deloitte recently published an article with the Wall Street Journal covering how AI is revolutionizing how humans work and its transformative impact. They emphasized that AI is not merely a resource or tool, but, that it serves almost as a co-worker, enhancing work processes and efficiency. This article discussed how the evolving form of intelligence augments human thinking and emphasized this as a catalyst for accelerated innovation.

Manufacturing is uniquely situated to benefit from AI to improve operations and empower their frontline workforces. The skilled labor gap has reached critical levels, and the market is under tremendous stress to keep up with growing consumer demand while staying compliant with quality and safety standards. Manufacturing workers are crucial to the success of operations – maintenance, quality control and assurance, and more – manufacturers rely upon their workforce to ensure production proceeds smoothly and successfully.

AI is playing a key role in changing the manufacturing landscape, augmenting workers and empowering them with improved, optimized processes, better data for informed decision-making, troubleshooting, personalized instructions and training, and improved quality assurance and control. According to the World Economic Forum, an estimated 87% of manufacturing companies have accelerated their digitalization over the past year, the IDC states 40% of digital transformations will be supported by AI, and a recent study from LNS Research found that 52% of industrial transformation (IX) leaders are deploying connected worker applications to help their frontline workforces. Not only that, AI technology is expected to create nearly 12 million more jobs in the manufacturing industry.

Integrating AI into manufacturing not only enhances productivity, but also opens the door to new possibilities for worker safety, training, and innovative new manufacturing practices. Here are some ways AI is transforming manufacturing operations:

  • AI-based Workforce Analytics: Collecting, analyzing, and using frontline worker data to assess individual and team performance, optimize upskilling and reskilling opportunities, increase engagement, reduce burnout, and boost productivity.
  • Personalized Training in the Flow of Work: With AI and connected worker solutions, manufacturers can identify and supply training at the time of need that is personalized to each individual and the task at hand.
  • Personalized Work Instructions: AI enables manufacturers to offer customized digital work instructions mapped to their skill levels and intelligently assign work based on each individual’s capabilities.
  • Digital Performance Support and Troubleshooting Guide: Generative AI assistants and bot-based AI virtual assistants offer support and guidance to manufacturing operators, enabling access to collaborative technologies and knowledge bases to ensure the correct actions and processes are taken.
  • Optimize Maintenance Programs: AI algorithms analyze data from sensors on machinery and other connected solutions to predict when equipment is likely to fail. This enables proactive maintenance, minimizing downtime and reducing maintenance costs. Additionally, with AI technologies, manufacturers can implement autonomous maintenance processes through a combination of digital work instructions and real-time collaboration tools. This allows operators to independently complete maintenance tasks at peak performance.
  • Improve Quality Control: AI-powered solutions can improve inspection accuracy and optimize quality control and assurance processes to identify defects faster. With connected worker solutions, manufacturers can effectively turn their frontline workforce into human sensors supplying quality data and enhancing assurance processes.
  • Ensure Worker Safety: AI-driven safety systems coupled with connected worker technologies monitor the work environment, supplying real-time data and identifying potential hazards to ensure a safer workplace for employees.

connected enterprise

As AI continues to advance, the manufacturing industry is poised for even greater transformation, improving both the quality of products and the working conditions for employees. AI is revolutionizing the way humans work and how the manufacturing industry approaches nearly every process across operations, augmenting work interactions, productivity, efficiency, and boosting innovation.

How to Improve Manufacturing Employee Onboarding

Augmentir’s take on the trending Workforce Institute’s staggering survey numbers.

Employee onboarding is crucial to any organization. It’s even more important in manufacturing, where workers have to understand complex operating procedures and accomplish tasks in a timely manner.

An employee’s first impression of a workplace can set the tone for their entire experience with the company. An engaging and informative onboarding process can improve job performance by setting up workers for success.

Plus, an employee is more likely to speak highly of the business they work for if they see themselves as a valuable member of the team.

If want to improve your manufacturing employee onboarding process, explore this article that goes over the following:

What is employee onboarding?

Employee onboarding is the process in which new hires are integrated into a company. It involves training activities, a new-hire orientation, and learning about the business’s structure, culture, mission and values.

Finding the right candidate for a position is the first step to building a successful team. Onboarding that new employee is the most important next step. Done right, this process can set the precedent for a productive, content and even excited worker.

The two main goals of the first day of onboarding should be to set clear employee expectations and introduce their objectives. Workers should know what their job duties and responsibilities are from the get-go.

How is onboarding different from employee orientation?

Onboarding is often confused with employee orientation. Orientation usually involves completing necessary paperwork, while the onboarding process is comprehensive and can last for months.

Employee orientation is a one-time event. Its purpose is to welcome new hires to a company and introduce a checklist of mandatory tasks to complete such as filling out forms.

Employee onboarding, meanwhile, consists of completing a series of activities, including orientation. It includes training over a longer period of time to help workers learn more about their roles, their teams and how their jobs relate to overarching company goals.

Both onboarding and orientation are critical aspects of introducing employees to their new work environment. They also complement each other in improving employee engagement.

How to effectively onboard new hires

Investing time in your workers is one of the best ways to retain employees and boost productivity.

A new hire’s first few weeks are some of the most important in setting up expectations and building their personal investment in your company.

Go above and beyond and you’ll reap the benefits. Overlook the onboarding experience and you could have unsatisfied employees.

Here are five ways to effectively onboard new hires:

Step 1: Create a worker playbook.

Start by giving a general overview of your business, including your mission, values and perks. Some things to include are:

  • Your customers and stakeholders
  • Work culture and expectations
  • Team members/employees
  • What company success and growth look like

Step 2: Set 90-day goals.

Giving new hires direction and actionable items from the start is important. Identify some goals to work towards to give employees the confidence to excel in the company.

Be sure to provide any resources they will need and connect employees with other workers who can help them. Having a clear plan will make it easier to track goals and collaborate with workers along the way.

Step 3: Set a time to meet and provide feedback.

Set aside time to meet with new hires to provide feedback and ask how they are doing. This can foster connectedness and engagement between you and your employee.

This also gives you the opportunity to learn more about your workers and address any concerns they may have.

It also lets you elicit employee observations of the company and its processes, which can be insightful. A new hire may offer ideas that people invested in the current paradigm wouldn’t think of.

Step 4: Outline schedule and job duties.

It’s crucial to set consistent work schedules to ensure productivity. Loose or frequently changing schedules can lead new hires to think your organization is disorganized.

Further, outlining job duties (such as required skills) can also give employees a sense of direction and ensure they have plenty to work on.

Consider digitizing your onboarding and training program to help accelerate the overall onboarding schedule and get your employees productive faster, and build a program that incorporates the following:

  • Job expectations
  • Performance evaluation
  • Role shadowing
  • Training opportunities
  • HR meetings/employee documentation
  • Compliance training
  • Ongoing assessment through quizzing

In time, new hires will have a better idea of their workload and how to create and execute their own daily task lists.

Step 5: Set up continuous learning opportunities.

The best results from onboarding come months after the process is over. That’s because setting up continuous employee learning opportunities fosters professional development.

A worker can take everything that they learned from the onboarding process and apply it to their day-to-day tasks. Give workers the support and guidance they need, at the moment of need, whether it’s immediate access to a digital troubleshooting guide, or connecting virtually with a subject matter expert. Delivering personalized work procedures for every worker allows for continuous learning and growth.

Why onboarding is important in manufacturing

Creating effective onboarding programs can boost employee engagement and create a manufacturing workforce that excels in industry-related skills.

Effective onboarding has also been shown to:

  • Reduce employee turnover
  • Cultivate existing and new skills
  • Integrate workers more quickly
  • Foster long-term employee satisfaction
  • Create the foundation for workforce development

Optimizing onboarding with connected worker technology

Many manufacturing companies are using modern connected worker technology to transform and optimize how they hire, onboard, train, and deliver on-the-job guidance and support. AI-based connected worker software provides a data-driven approach that helps train, guide, and support today’s dynamic workforces by combining digital work instructions, remote collaboration, and advanced on-the-job training capabilities.

As workers become more connected, manufacturers have access to a new rich source of activity, execution, and tribal data, and with proper digital tools can gain insights into areas where the largest improvement opportunities exist. Today’s workers embrace change and expect technology, support and modern tools to help them do their jobs.

Augmentir’s AI-based connected worker solution delivers continuous learning and development tools to optimize onboarding training for a rapidly changing and diverse workforce.

Built-in reporting for skills management and job proficiency allows you to accurately track and manage skills, certifications, and qualifications for your team. AI-based analytics help you better understand your workforce and make informed workforce development decisions.

intelligently assign jobs

Find out how our software can make it easier to onboard new employees and set them up for success. Contact us today to arrange a demo.

How to Build a World Class Supply Chain

Connected frontline operations platforms are helping manufacturers reduce downtime and provide a foundation for a holistic preventive maintenance strategy.

Your supply chain turns raw materials into finished products that meet customer expectations. It takes a whole network of people, from suppliers and manufacturers to distributors and partners, working together to produce the best quality products on the market. But how is it possible to build a “world class” supply chain?

According to Harvard Business Review, recent events such as the Covid-19 pandemic have exposed supply chain vulnerabilities and prompted a reevaluation of global approaches to improve resilience. Fortunately, the idea of a supply chain being world-class goes hand in hand with world class manufacturing, and there is a set of guiding principles to follow. Following them will help you successfully operate and manage a manufacturing firm that can remain competitive in the global marketplace.

world class supply chain

In this article, you’ll learn the five steps for building a world class supply chain and how Augmentir can help you transform the process:

  • 5 steps for making your supply chain world class
    • Step 1: Define clear objectives
    • Step 2: Gather necessary data
    • Step 3: Choose a supply chain management system
    • Step 4: Conduct supply chain network analysis
    • Step 5: Refine and improve
  • Elements of world class supply chain management and how Augmentir can help

5 steps for making your supply chain world class

Making your supply chain world class is about meeting or even exceeding customer expectations and delivering top-notch performance every time.

Step 1: Define clear objectives

Start by identifying overarching goals that will create consumer satisfaction. To help define those goals, ask yourself the following questions:

  • How much inventory needs to be stored, and where should it be?
  • Which modes of transportation would best balance out cost versus customer service objectives?
  • Which warehouses should administer which products to people?
  • How many warehouses are needed and what is the role of each?
  • What are the best routes to get products to customers the fastest?

Step 2: Gather necessary data

It’s important to gather the appropriate data to ensure that you’re meeting company-specific goals. For example, you may track data so you can keep an eye on product demand, transportation rates, lead times, and warehouse and inventory expenses.

Step 3: Embrace technology and digitalization

Leverage technology to automate manual tasks, improve visibility, and enhance decision-making. It’s crucial to pick software that addresses all of your production criteria and facilitates your unique business model. Adopt advanced supply chain management systems (SCM), enterprise resource planning (ERP) software, connected worker software, and warehouse management systems (WMS). Explore emerging technologies like blockchain, AI, and robotics to further optimize operations.

Step 4: Conduct supply chain network analysis

Once you’ve picked the perfect supply chain software, it’s time to analyze how well your production processes are faring. Consider evaluating if there are any gaps in product development and how long it takes for goods to be delivered.

Step 5: Refine and continually improve

Carefully examining your supply chain network and processes is a great starting point for becoming world class. But if you don’t make steady strides toward improvement, you’re left at a standstill. Things are constantly evolving in the manufacturing industry, so it’s helpful to check some of the following: production capacity, price fluctuations in raw materials, and any new large customer orders (especially if they were added in a different location).

Encourage a culture of learning, innovation, and continuous improvement within the organization. Promote employee engagement, provide training and development opportunities, and empower employees to contribute ideas for process optimization and supply chain innovation.

Continuous improvement is a must. So revisit your processes regularly, whether that’s monthly, quarterly, or annually.

Elements of world class supply chain management and how Augmentir can help

Implementing a world class supply chain management system can change the way manufacturers handle daily operations.

A world class supply chain usually is:

  • Customer focused: Consumers should be at the forefront of all production activities to ensure that goods are being made and sold in a timely, cost-effective manner.
  • Adaptable to changes: The manufacturing industry is changing fast, so manufacturers have to be responsive to changing customer demands, market factors, and more.
  • Collaborative: An effective supply chain fosters strong relationships among manufacturers, suppliers, distributors, and customers.
  • Highly efficient: Incorporating streamlined production processes, smart tech, and other resources is crucial to stand out among competitors.
  • Innovative: Constantly improving procedures drives growth and innovation.
  • Sustainable: Implementing sustainable techniques for cutting waste and maximizing productivity can lead to significant savings over time.

 

This is where Augmentir can help. We offer the world’s first AI-powered connected worker solution that advances how manufacturing firms handle day-to-day supply chain and other operations.

manufacturing kpi first time right

Our software lets you provide digital standard operating procedures for how to complete routine tasks and get the most out of worker output and productivity. We’ve helped frontline workers reduce training and rework time by 76%, and increase productivity levels by 36%.

With our software, you can build a world class supply chain that empowers workers across departments to make and deliver products of the highest quality. Request a live demo to learn more on how we’re the right fit for you!

Paperless Manufacturing: Your Guide to Transitioning to a Paperless Factory

Learn how to digitize your operations and build a paperless factory in this paperless manufacturing guide from Augmentir.

Manually managing and tracking production in manufacturing has become a thing of the past. That’s because manufacturers are adopting a new digital approach: paperless manufacturing.

Paperless manufacturing uses software to manage shop floor execution, digitize work instructions, execute workflows, automate record-keeping and scheduling, and communicate with shop floor employees. More recently, this approach also digitizes skills tracking and performance assessments for shop floor workers to help optimize workforce onboarding, training, and ongoing management. This technology is made up of cloud-based software, mobile and wearable technology, artificial intelligence, machine learning algorithms, and advanced analytics.

More recently, your journey to paperless manufacturing is being accelerated through the availability of generative AI assistants and supporting import tools that can streamline the conversion of existing content into interactive, mobile-ready content for your frontline teams.

paperless manufacturing and digital factory

Paperless manufacturing software uses interactive screens, dashboards, data collection, sensors, and reporting filters to show real-time insights into your factory operations. If you want to learn more about paperless manufacturing processes, explore this guide to learn about the following:

What is a paperless factory?

A paperless factory uses AI-powered software to manage production, keep track of records, and optimize jobs being executed on the shop floor. Paperless manufacturing is intended to replace written record-keeping as well as paper-based work instructions, checklists, and SOPs, and keep track of records digitally.

For example, in most manufacturing operations, everything from quality inspections to operator rounds and planned and autonomous maintenance is done on a regular basis to make sure factory equipment is operating properly and quality and safety standards are met. In most manufacturing plants, these activities are done manually with paper-based instructions, checklists, or forms.

Operators and shop floor workers in paperless factories use software to execute work procedures and see production tasks in ordered sequences, which enables them to implement tasks accordingly. Workers are able to view operating procedures, or digital work instructions, using mobile devices (wearables, tablets, etc.) in real-time.

benefits of digital work instructions

Furthermore, paperless manufacturing incorporates the digitization of shop floor training, skills tracking, certifications, and assessments.  This digital approach uses skills management software helps optimize HR-based processes that were previously managed via paper or spreadsheets, and includes the ability to:

  • Create, track, and manage employee skills
  • Instantly visualize the skills gaps in your team
  • Schedule or assign jobs based on worker skill level and proficiency
  • Close skill gaps with continuous learning
  • Make data-driven drive operational decisions

digital skills management in a paperless factory

What are the benefits of going paperless in manufacturing?

There are a number of reasons for factories to go paperless, from cost-effectiveness to increased productivity and sustainability. A paperless system can revolutionize production processes, workforce management, and business operations.

Here are the top benefits of going paperless:

  1. Accelerate employee onboarding: By digitizing onboarding and moving training into the flow of work, manufacturers can reduce new hire onboarding time by 82%.
  2. Increase productivity: Digitizing manufacturing operations means no more manual, paper-based data collection or record-keeping. Workers have more time to run their equipment, execute shop floor tasks, and find solutions to problems.
  3. Boost data accuracy: People are prone to making mistakes, but digital data capture and validation can help offset human error and improve accuracy.
  4. Improved workforce management: Digital skills tracking and AI-based workforce analytics can help optimize production operations and maximize worker output.
  5. Manage real-time operations: Human-machine interface systems eliminate the need for paper, files, and job tickets. This means that workers can analyze inventory and other data in real-time.
  6. Save money: Although going paperless means that the cost of paper is eliminated, the savings extend beyond that. With greater productivity, operations in real-time, and improved production optimization, costs can be reduced in many areas.

How do you go paperless in manufacturing?

Going paperless starts with digitizing activities across the factory floor to increase productivity, and extending that value through a digital connection between the shop floor and enterprise manufacturing systems. We lay out below the four basic steps for how to go paperless in manufacturing:

Step 1: Digitize your existing content with Gen AI and Connected Worker technology.

Paperless manufacturing starts with the use of modern, digital tools that can quickly and easily digitize and convert your existing paper-based content. Tools like Augmentir’s Augie™, a generative AI suite of technologies, helps you import and convert existing content regardless of format. Once converted, Connected Worker solutions that incorporate enhanced mobile capabilities and combine training and skills tracking with connected worker technology and on-the-job digital guidance can deliver significant additional value. A key requirement to start is to identify high-value use cases that can benefit from digitization, such as quality control or inspection procedures, lockout tagout procedures, safety reporting, layered process audits, or autonomous maintenance procedures.

Pro Tip

You can now import existing PDF, Word, or Excel documents (just like the PDF above) directly into Augmentir to create digital, interactive work procedures and checklists using Augie™, a Generative AI content creation tool from Augmentir. Learn more about Augie – your industrial Generative AI Assistant.

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Step 2: Augment your workers with AI and Connected Worker technology.

AI-based connected worker solutions can help both digitize work instructions and deliver that guidance in a way that is personalized to the individual worker and their performance. AI Bots that leverage generative AI and GPT-like AI models can assist workers with language translation, feedback, on-demand answers, access to knowledge through natural language, and provide a comprehensive digital performance support tool.

As workers become more connected, companies have access to a rich source of job activity, execution, and tribal data, and with proper AI tools can gain insights into areas where the largest improvement opportunities exist.

Step 3: Set up IoT sensors for machine health monitoring.

The industrial Internet of Things (IoT) uses sensors to boost manufacturing processes. IoT sensors are connected through the web using wireless or 4G/5G networks to transmit data right from the shop floor. The use of machine health monitoring tools along with connected worker technology can provide a comprehensive shop floor solution.

Step 4: Connect your frontline to your enterprise.

Digitally connected frontline operations solutions not only enable industrial companies to digitize work instructions, checklists, and SOPs, but also allow them to create digital workflows and integrations that fully incorporate the frontline workers into the digital thread of their business.

The digital thread represents a connected data flow across a manufacturing enterprise – including people, systems, and machines. By incorporating the activities and data from these previously disconnected workers, business processes are accelerated, and this new source of data provides newfound opportunities for innovation and improvement.

 

Augmentir provides a unique Connected Worker solution that uses AI to help manufacturing companies intelligently onboard, train, guide, and support frontline workers so each worker can contribute at their individual best, helping achieve production goals in today’s era of workforce disruption.

Our solution is a SaaS-based suite of software tools that helps customers digitize and optimize all frontline processes including Autonomous and Preventive Maintenance, Quality, Safety, and Assembly.

paperless factory

 

Transform how your company runs its frontline operations. Request a live demo today!

 

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Augmentir Wins Gold at 2024 Brandon Hall Group Excellence in Technology Awards

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Augmentir recognized by the Brandon Hall Group for the “Best Advance in Generative AI for Business Impact”, wins gold in the 2024 Technology Excellence Awards.

We did it again!

We are excited to announce today that Augmentir won Gold in the 2024 Brandon Hall Group Excellence in Technology Awards for “Best Advance in Generative AI for Business Impact“.

augmentir wins gold at 2024 brandon hall group awards for generative ai business impact

The 2024 Brandon Hall Group Excellence in Awards™ are given for work in Learning and Development, Talent Management, Talent Acquisition, Human Resources, Sales Enablement, Future of Work, and Education Technology. Augmentir received its gold award in the Future of Work category based on our breakthrough, innovative use of Generative AI to address skilled labor shortages and workforce challenges that are crippling the manufacturing industry today.

Entries were evaluated by a panel of veteran, independent senior industry experts, Brandon Hall Group analysts, and executives based upon these criteria: fit the need, program design, functionality, innovation, and overall measurable benefits.

“In our 31st year, the Excellence in Technology Awards continue to showcase the best innovations in learning, talent management, talent acquisition, HR, workforce management, and sales enablement technologies. We are proud to receive applications from a diverse range of organizations globally, reflecting the ever-evolving landscape of technology solutions,” said Brandon Hall Group Chief Operating Officer Rachel Cooke, leader of the Excellence Awards program.

 

Augmentir’s generative AI solution – Augie™ – is a central component to the Augmentir Connected Worker platform. Augie is a generative AI assistant that improves operational efficiency and supports today’s less experienced frontline workforce through faster problem-solving, proactive insights, data analysis, rapid content creation, and enhanced decision-making.

Augmentir recently unveiled powerful new updates to Augie, and launched the industry’s first Industrial Generative AI Suite, targeted towards improving safety, quality, and productivity for the industrial frontline workforce. Augie’s suite of gen AI services expand on the platform’s existing capabilities, which have been in use by leading manufacturers for over a year, transforming operations and addressing the skilled labor shortage through advanced troubleshooting and real-time digital assistance to frontline workers. The Augie Industrial Gen AI Suite includes:

  • Augie Industrial Work Assistant
    Provide real-time support and guidance to workers on the floor or in the field. Augie helps workers with standard work, troubleshooting, and information access.
  • Augie Content Assistant
    Automatically convert existing digital content (Word Excel, PDF, etc) into native Augmentir Work instructions, SOPs, OPLs, CILs, Checklists, etc., accelerating deployment. Generate training, checklists, and quizzes from a wide range of source types including images, manuals, free-form tests, etc., to streamline worker training and onboarding.
  • Augie Data Assistant
    Augie provides insights from any source of operational data, including standard datasets such as Skills, Standard Work, Safety, and Work Execution, as well as customer-specific datasets generated through Augmentir’s report configurator. Augie eliminates the need for “report writing” and through its conversational interface answers questions, performs math, and generates graphical reports, increasing responsiveness.
  • Augie Extensibility Assistant
    Augie increases the productivity of developers building new functions and supporting existing user-defined functions within Augmentir’s extensibility framework. Augmentir’s unique Platform-as-a-Service offering empowers customers and partners to create unique solutions that solve critical business challenges—a capability that no other platform on the market offers.
  • Augie Industrial GenAI-as-a-Service
    As an industry first, Augie exposes its GenAI capabilities as APIs within Augmentir’s extensibility framework. This allows companies and partners to create innovative, customized GenAI solutions tailored to business, or industry-specific needs and use cases. Commonly used APIs include: translateText enabling on-the-fly translation of dynamic content, and imageQA, enabling direct comparison or summarization of images, supporting critical applications in Quality, Safety, and Operations.

“We’re thrilled to be recognized by the Brandon Hall Group for bringing the transformative power of generative AI to industrial frontline operational processes,” said Russ Fadel, CEO of Augmentir. “Just as we have seen GenAI deliver transformational value to the consumer and enterprise, the Augie Suite provides the tools to enable companies to empower their frontline workers, regardless of experience, to perform with higher levels of safety and productivity. Additionally, this provides the tools for our partners to build innovative use cases to solve previously unsolvable problems.”

Augmentir introduced Augie in early 2023, becoming the first software provider in the manufacturing sector to offer a generative AI solution focused on the industrial frontline workforce. Since its launch, Augie has been adopted by industry leaders across all manufacturing and production verticals, helping prevent safety and quality issues at the point of work, driving operational efficiency, and giving frontline workers the tools, guidance, and support they need to do their best work.

Augie’s generative AI capabilities are built into the core of the Augmentir platform, so customers can quickly and securely leverage the latest AI advances within the framework of digital collaboration, skills management, and work execution. This allows customers to leverage existing data, documents, applications, and their existing tribal knowledge, increasing their ROI.

Interested in learning more?

If you’d like to learn more about Augmentir and see how our AI-powered connected worker platform enables Augmented Connected Worker initiatives to improve safety, quality, and productivity across your workforce, schedule a demo with one of our product experts.

 

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How to reduce downtime and increase productivity in manufacturing

Connected frontline operations platforms are helping manufacturers reduce downtime and provide a foundation for a holistic preventive maintenance strategy.

Downtime in manufacturing refers to a period of time when a production line or machine is not in operation due to maintenance, repairs, or other issues. This can result in a loss of productivity, increased costs, and missed production targets, and it is estimated that in the US alone it costs manufacturers around $1 trillion dollars per year. Not surprisingly, the biggest factors that contribute to unplanned downtime are human error and improper maintenance.

To minimize downtime, manufacturers are turning to digital technology to transform their frontline operations and provide a foundation for a holistic preventive maintenance strategy.

reduce downtime in manufacturing

Reducing downtime with a Connected Frontline Operations Platform

Manufacturers often implement Total Productive Maintenance (TPM) as part of a more comprehensive preventive maintenance approach. TPM is a strategy commonly used in manufacturing and production operations to improve the effectiveness and reliability of equipment, which in turn can increase productivity and reduce downtime.

Total productive maintenance strives to reduce workplace losses by placing the responsibility of basic maintenance upkeep on the primary equipment user: the machine operator. This preventive practice consists of “8 pillars” to help improve equipment reliability and elevate worker productivity:

Autonomous Maintenance as pillar of TPM

At the front of this framework is Autonomous Maintenance. Autonomous maintenance is a technique used in TPM that involves giving operators and other frontline employees the responsibility and authority to take care of their own equipment and work areas (e.g cleaning, safety checks, etc.). This can improve employee engagement by giving them a sense of ownership over their work and equipment, as well as a greater understanding of how their actions can impact productivity and quality. Additionally, involving employees in the maintenance process can lead to improved communication and teamwork, which can further enhance engagement.

This is where frontline operations platforms come into play.

Connected frontline operations platforms are digital software tools that can help standardize and improve the way operators perform maintenance tasks. They are used to improve communication, training, collaboration, guidance, and support for the operators.

Reduce machine downtime with Augmentir’s Connected Worker Solution

See how Augmentir can help you implement an effective autonomous maintenance program and optimize your frontline operations.

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downtime dashboard

Your connected workforce – a key to reducing downtime

Factory workers can have a significant impact on downtime in manufacturing. Whether it’s due to mistakes made by operators, non-optimal scheduling, or lack of communication, your workforce is at the center of your frontline operations. Factory workers can impact downtime in a variety of ways:

  1. Improper operation or maintenance: If factory workers are not properly trained on how to operate and maintain equipment, they may inadvertently cause downtime by making mistakes or not following proper procedures. Modern connected worker tools, like Augmentir’s connected worker solution, are increasingly being used to streamline training and digitize skills tracking to help ensure that the right people with the right skills are on the job.
  2. Safety incidents: Workers who do not follow proper safety procedures can cause accidents that lead to downtime while equipment is repaired or replaced. By digitizing safety procedures, manufacturers can ensure that workers perform the proper steps, and follow the proper protocols before performing a maintenance routine.
  3. Human error: Workers may make mistakes that lead to downtime, such as not properly setting up equipment or not noticing when a machine needs maintenance. Properly training employees on how to maintain and operate equipment can help to minimize downtime due to human error
  4. Quality issues: Workers may produce products that do not meet quality standards, which can lead to downtime while the products are reworked or scrapped.
  5. Lack of proper communication: Having clear and effective communication channels can help to quickly identify and address any issues that arise. Frontline communication tools like Augmentir can help improve communication and digitally record issues to better understand root causes. By identifying the underlying causes of downtime, manufacturers can take steps to prevent similar issues from occurring in the future.
  6. High turnover rate: High turnover rate can lead to a lack of experienced workers and can cause downtime while new employees are trained. While it’s difficult to completely prevent a high turnover rate, you can take measures to both expedite training for new hires, as well as create a more engaged, more empowered workforce. For example, Augmentir’s connected worker solution helps to accelerate new hire training and onboarding, and provides a skills management framework that helps to ensure that workers are excelling at their jobs.

It is important to note that factory workers are a crucial part of the manufacturing process and their role is vital for the success of the business. However, by providing workers with proper training, safety procedures, and communication channels, downtime in manufacturing due to human error can be reduced. Additionally, involving workers in the decision-making process and continuous improvement initiatives, can help to increase their ownership and responsibility towards the equipment, processes, and the whole factory’s performance.

Interested in learning more?

Augmentir is a connected worker solution that allows industrial companies to digitize and optimize all frontline processes that are part of their TPM strategy. The complete suite of tools are built on top of Augmentir’s patented Smart AI foundation, which helps identify patterns and areas for continuous improvement.

manufacturing kpi first time right

 

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