Connected frontline operations platforms are helping manufacturers reduce downtime and provide a foundation for a holistic preventive maintenance strategy.
Centerlining in manufacturing is a methodology that uses standardized process settings to assure that all shop floor operations are carried out consistently.
For example, in manufacturing, it pinpoints which machine settings are needed to execute a given process and ensures operators implement those settings to avoid any defects on the shop floor. This works to decrease product and procedure discrepancies by improving machine efficiency.
The type of machine configurations that can be centerlined to create quality goods that meet customer expectations range from temperature, speed, and pressure settings to the proper alignment of guard rails. When applied to a procedure, centerlining can substantially increase the number of sellable items, secure uniform product quality, and decrease production costs.
In a nutshell, employing a successful centerlining process can help optimize plant operations and reduce mistakes in product creation.
Learn more about how centerlining can improve everyday operations, and how to centerline a manufacturing process to yield the best output, in the following sections:
Centerlining works by using specific machine settings per product (pressure, speed, temperature, etc.) to ensure processes are carried out the same way during each assembly line run.
Using the right centerline settings also has a side benefit: it lets operators identify problems as they happen. If workers know which process variables are triggering production delays, they can better control them to boost product quality output.
This can be achieved by creating a statistical process control chart to see which variables are causing interruptions to the assembly line and make any needed changes to the process. Creating a chart can also help workers identify procedures that are affecting the development of goods to ensure continuous improvement.
Centerlining goes hand in hand with total productive maintenance (TPM), a method which utilizes equipment, machine operators, and supporting processes to boost the quality and safety of production protocols.
How manufacturing efficiency can be improved by centerlining
Standardizing the appropriate machine settings can make everyday operations run more smoothly. For example, centerlining the requirements for each product can streamline changeovers, allowing workers to quickly reset their equipment and not lose time when switching to a new product run. This can prevent costly mistakes and reduce waste throughout the shop floor.
It also guarantees that all processes are completed in the same manner. Consistency helps ensure quality, especially when operators are setting up equipment for a production run. Failing to configure the right settings can increase the time for product changeovers and cause product deficiencies.
How to centerline a manufacturing process
Centerlining in manufacturing is a great way to troubleshoot product and procedure variations, oversee operations, and carry out statistical analysis to boost quality assurance and control.
Learn how to centerline a process by following the four steps below.
Step 1: Determine key process variables
It’s crucial to spot process variables that have the greatest effect on product quality to minimize any defects. Potential variables can include pressure, temperature, density, mass, and more.
Step 2: Identify machine settings for each variable
Then, look at which centerline settings can be applied to each process to ensure the creation of quality goods. Again, you’ll want to determine what has worked well in the past and use a statistical process control chart to set variable limits.
Important things to consider are: when the process has worked, which setting was best suited for that procedure, and how the two worked in conjunction with one another.
Step 3: Assess variable impact on production process and product
After you’ve identified the appropriate machine settings, it’s time to monitor how each variable impacts the production process and final product creation. Start by analyzing which assembly line runs yielded the highest production rate, factoring in things like equipment idle time, scrapped parts, rework, etc., to gauge what works and what needs improvement.
It’s vital that you have accurate, clear data to analyze. We recommend digitizing your centerlining process and results to correctly quantify the performance of each variable.
Step 4: Ensure centerline settings are always applied
Lastly, make sure that all operators are aware of and educated on how to best implement a centerlining process so that the right settings are applied each time. Failure to do so can result in mistakes and product deficiencies down the line. It’s best to provide all the necessary resources, steps, and training from the get-go to avoid costly errors. Digital work instructions and connected worker tools are a great way to ensure that operators are properly equipped to perform centerlining procedures.
At this stage, your manufacturing firm should have the proper reporting techniques to evaluate product quality against centerline procedures.
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.
Learn how to improve manufacturing shift handover with our downloadable template and AI-powered connected worker solution.
The manufacturing world is at an exciting yet challenging crossroads. Deloitte’s 2025 Manufacturing Industry Outlook paints a vivid picture of the road ahead—one filled with hurdles like labor shortages and rising input costs but also brimming with opportunities driven by digital transformation and innovation. At Augmentir, we see this journey every day through our work with industry leaders, and we’re thrilled to share how our AI platform is helping manufacturers navigate these challenges with confidence and creativity.
Deloitte’s report doesn’t just forecast trends; it highlights the critical role technology plays in shaping the future. For us at Augmentir, this is more than just a validation of our work. It’s a call to action—an affirmation that we’re on the right path to empowering manufacturers with AI to build smarter, more resilient operations. Let’s dive deeper into how Augmentir’s AI platform, and specifically Augie, our Industrial Generative AI Suite, aligns with Deloitte’s vision and how we’re enabling our partners to seize the opportunities ahead.
Tackling Labor Shortages and Value Chain Disruptions
Labor shortages are no longer hypothetical scenarios or statistical warnings—they’re the daily reality for manufacturers. Deloitte’s report underscores the urgency of addressing these workforce challenges, and at Augmentir, we’re ready to help.
Our industrial Gen AI assistant, Augie, goes beyond just numbers. Yes, it forecasts workforce needs and optimizes staffing levels, ensuring that resources are allocated precisely where they’re needed. But it also does something more profound: it prioritizes people. By streamlining talent management and offering actionable workforce planning insights, Augie helps manufacturers foster environments where employees feel valued and empowered. A happy and engaged workforce is the backbone of any successful operation, and that’s why our solutions are designed to enhance satisfaction and retention alongside productivity.
Supply chain disruptions, another thorn in the industry’s side, are no match for Augie’s analytical prowess. By delivering real-time insights and actionable recommendations, Augmentir helps manufacturers proactively address potential bottlenecks and ensure operational resilience. With Augie, labor and value chain challenges transform from overwhelming obstacles into manageable opportunities.
Managing Rising Input Costs and Enhancing Efficiency
The pressure of rising costs—whether from raw materials or wages—is a constant battle for manufacturers. Every dollar saved can make a monumental difference, but achieving savings without sacrificing quality is a delicate balance. That’s where Augie excels.
Imagine having a personal advisor who’s always on the lookout for ways to optimize your operations. That’s Augie. By analyzing market trends and production data, Augie offers insights into cost-saving opportunities and ways to enhance efficiency. These aren’t generic, one-size-fits-all solutions—they’re tailored recommendations that align with your specific goals.
From optimizing supply chains to fine-tuning production processes, Augie empowers manufacturers to navigate the complexities of rising costs while staying competitive. The result? Greater operational efficiency, better resource allocation, and a clear pathway to long-term sustainability. In today’s fast-paced market, those aren’t just advantages; they’re necessities.
Embracing Smart Operations Through Digital Transformation
The future of manufacturing is undeniably digital, and Deloitte’s report emphasizes the transformative potential of technologies like AI and cloud computing. At Augmentir, we’re not just advocates for digital transformation—we’re enablers.
Augie seamlessly integrates with cutting-edge technologies, enabling manufacturers to unlock the full potential of smart operations. By embracing tools like generative AI and IoT, manufacturers can improve efficiency, foster innovation, and gain a competitive edge. But digital transformation isn’t just about adopting new tools; it’s about rethinking processes and strategies to drive meaningful change. That’s where Augie shines—bridging the gap between traditional manufacturing and the smart factories of tomorrow.
When manufacturers adopt a digital-first mindset, they’re not just investing in technology—they’re investing in growth, resilience, and innovation. And with Augie by their side, that transformation becomes not just achievable but inevitable.
Driving Strategic Innovation and Investment
Innovation is the lifeblood of manufacturing, but with countless technologies vying for attention, choosing the right investments can feel overwhelming. Augie simplifies this process by offering data-driven insights into the areas with the highest potential return.
Whether it’s advanced AI, extended reality, or cutting-edge simulation tools, Augie helps manufacturers make informed decisions that align with their strategic goals. From optimizing production lines to enhancing workforce training, Augie ensures that technology investments deliver tangible, meaningful results.
This isn’t just about staying ahead of the competition—it’s about driving innovation that meets customer demands, supports sustainability, and creates lasting value. With Augie, manufacturers have the clarity and confidence they need to make investments that matter.
Looking Ahead
Deloitte’s 2025 Manufacturing Industry Outlook offers a vision of both challenge and opportunity, and we at Augmentir couldn’t be more excited about the road ahead. The future of manufacturing is one of resilience, efficiency, and innovation—and AI is the key to unlocking it.
With Augie, manufacturers can tackle their toughest challenges and turn them into opportunities for growth. From labor shortages to rising costs, from digital transformation to strategic innovation, Augie is more than just a tool—it’s a trusted partner in navigating the complexities of the modern manufacturing landscape.
Are you ready to transform your operations and embrace the future of manufacturing? Let’s connect. Together, we can build a smarter, stronger, and more sustainable industry that thrives in the face of change.
https://www.augmentir.com/wp-content/uploads/2025/01/2025-manufacturing-industry-outlook.webp12602400Chris Kuntzhttps://www.augmentir.com/wp-content/uploads/2021/09/Augmentir_Logo_Sm-300x169.pngChris Kuntz2025-01-29 13:19:442025-01-29 13:19:44A Response to Deloitte's 2025 Manufacturing Industry Outlook from Augmentir
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.
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.
https://www.augmentir.com/wp-content/uploads/2024/04/packaging-industry-connected-workforce.webp6301200Chris Kuntzhttps://www.augmentir.com/wp-content/uploads/2021/09/Augmentir_Logo_Sm-300x169.pngChris Kuntz2024-04-07 18:34:312025-01-29 12:32:24How AI and the Augmented Connected Workforce is Revolutionizing the Packaging Industry
LNS Research reviewed dozens of Connected Frontline Worker (CFW) vendors, ranking Augmentir as the leading CFW solution innovator.
Efforts to enable the frontline industrial workforce through connected worker and other digital technologies have become increasingly common over the past several years, recently, LNS Research found that over half of industrial organizations globally have undertaken Connected Frontline Workforce (CFW) initiatives. CFW has become a strategic part of Industrial Transformation (IX) initiatives as manufacturers seek to solve critical labor shortages, skills gaps, and retention issues in frontline operations.
CFW-enabling technologies hold the promise of helping companies meet their frontline workforce challenges while optimizing operational performance across safety, quality, and productivity dimensions. However, industrial business and technology leaders must navigate the uncertain waters of the relatively immature and highly fragmented CFW Applications market to capture the opportunity fully.
From their extensive analysis, LNS Research has created the CFW Applications Solution Selection Matrix™ (SSM) – a comprehensive guide intended to help manufacturers better understand, evaluate, and even select from a shortlist of Connected Frontline Worker technology vendors.
LNS Research reviewed dozens of vendors within the CFW ecosystem and categorized them based on various key criteria, including product capabilities, market potential, and company presence. Augmentir was named by LNS Research as a leading CFW solution innovator in their SSM.
Augmentir positioned as a leading front runner and innovator
According to LNS Research, Augmentir is well-positioned for future growth, with a trajectory that gives it the potential to be among a small set of likely market leaders in the Connected Frontline Worker (CFW) Applications space. This assessment is based partly on the strength of differentiated capabilities of its AI-enabled solution suite to enable proactive, data-driven performance improvement, personalization of work execution support and training, and the integration of individual and team skills and qualifications to guide workforce development and shift-specific work assignment.
Other key factors impacting Augmentir’s potential are the strength and proven experience of the leadership and management teams, strong momentum in the market, a record of successful product innovation, ecosystem partnerships, and likely continued access to adequate funding and resources to support the expansion of go-to-market initiatives. Augmentir’s track record indicates a strong likelihood of continued growth and the potential over time to be among a select group of market leaders in the CFW Applications space.
Manufacturers are using connected frontline worker solutions as a foundation to their industrial transformation strategy to empower their employees with real-time, actionable data; driving better decision-making and improving safety, training, and more.
Leading manufacturers that deployed Augmentir’s AI-driven, smart, connected worker solution have seen impressive results, such as:
75% reduction in new hire training/onboarding time
27% reduction in machine downtime using Autonomous Maintenance
32% improvement in worker productivity
In addition to the above results, our customers have seen quality, safety, and productivity increases across all operations, as well as increases in employee retention and reductions in operating costs associated with employee churn.
If you are interested in learning why LNS Research ranked Augmentir as the leading connected worker solution in the market, reach out to us and request a live demo.
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.
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.
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.
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.
https://www.augmentir.com/wp-content/uploads/2024/03/evolution-of-ai-in-manufacturing.webp6301200Chris Kuntzhttps://www.augmentir.com/wp-content/uploads/2021/09/Augmentir_Logo_Sm-300x169.pngChris Kuntz2024-03-23 02:00:412025-01-13 12:01:40The Evolution of AI 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.
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.
https://www.augmentir.com/wp-content/uploads/2023/09/ai-revolutionizing-how-humans-work-in-manufacturing.webp6301200Chris Kuntzhttps://www.augmentir.com/wp-content/uploads/2021/09/Augmentir_Logo_Sm-300x169.pngChris Kuntz2023-09-21 13:00:582025-01-13 11:59:52AI: Revolutionizing How Humans Work in Manufacturing
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:
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.
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.
https://www.augmentir.com/wp-content/uploads/2022/08/how-to-improve-manufacturing-employee-onboarding.jpg6301200Chris Kuntzhttps://www.augmentir.com/wp-content/uploads/2021/09/Augmentir_Logo_Sm-300x169.pngChris Kuntz2022-08-01 13:45:322024-12-20 18:11:46How to Improve Manufacturing Employee Onboarding
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.
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.
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!
https://www.augmentir.com/wp-content/uploads/2023/06/world-class-supply-chain.png6301200Chris Kuntzhttps://www.augmentir.com/wp-content/uploads/2021/09/Augmentir_Logo_Sm-300x169.pngChris Kuntz2023-06-03 02:22:142024-12-20 18:05:13How to Build a World Class Supply Chain