Learn the difference between skills development and training in manufacturing, how they are important, and how the management of them can be improved through continuous learning methodologies and emerging technology.

At first glance, training and skills development seem synonymous and are often used interchangeably, but they have different purposes and goals. However, despite these differences, both are equally important for every organization, especially in the case of the manufacturing industry. According to Training Magazine, 57% of manufacturing organizations reported training and workforce development budget increases to address the widening skills gap and the skilled labor shortage.

the difference between skills development and training in manufacturing

At the most basic level, training is the process companies use to build the skills of new employees so they’re well-equipped to perform the role that they were hired for. While skills development, on the other hand, includes ongoing education, mentoring, and professional experiences that help employees grow into future roles and opportunities.

Both are extremely valuable to overall organizational growth and success, however, it’s important to apply them at the right time and in the right way. Read more on both skills development and training in manufacturing, why they are important, and how they can be improved and enhanced through the proper application of learning technology:

What is Skills Development in Manufacturing

Skills development goes beyond training by aiming to enhance a broader set of competencies and capabilities. It focuses on building a more well-rounded and adaptable workforce encompassing not only the acquisition of specific skills, but also the improvement of problem-solving abilities, critical thinking, creativity, adaptability, and continuous learning.

Skills development in manufacturing refers to the process of enhancing the knowledge, abilities, and competencies of individuals involved in the manufacturing process. It involves providing training and education to workers, engineers, and technicians to improve their technical, operational, and problem-solving skills. By providing training and development opportunities, manufacturing organizations can ensure that their workforce possesses the necessary skills and knowledge to perform their jobs effectively and efficiently.

skills management and training software for manufacturing

Many manufacturing industries face a shortage of skilled workers. Skills development programs help bridge the gap by training existing employees or new hires in the required competencies.

Overall, skills development in manufacturing is crucial for maintaining competitiveness in a rapidly changing industry. It ensures that the workforce remains adaptable, skilled, and capable of meeting the evolving demands of modern manufacturing processes.

Pro Tip

Implementing skills management software programs allow manufacturing organizations to digitize and effectively track worker skills, development progress, and intelligently assign work based on skills competencies, improving work allocation and workforce utilization.


What is Training in Manufacturing

Training in manufacturing primarily focuses on imparting specific knowledge, skills, or information to individuals. It often involves structured and organized programs designed to teach employees how to perform specific tasks or operate machinery and equipment. Training is often of shorter duration and may be task-specific or role-specific. It is designed to quickly bring employees up to a certain proficiency level in their current job.

The specific type of training required in manufacturing depends on the roles and responsibilities of the individuals involved, the company’s processes, and the industry in which they operate. Training in manufacturing is essential for several reasons:

  • Safety: Manufacturing processes often involve machinery, equipment, and materials that can be hazardous. Proper training ensures that employees understand and follow safety protocols, reducing the risk of accidents and injuries.
  • Quality Control: Quality in manufacturing is a critical, essential factor. Training programs teach employees how to maintain consistent product quality through accurate measurements, inspections, and adherence to quality standards.
  • Operational Efficiency: Training helps employees become more efficient in their tasks, reducing downtime, minimizing waste, and optimizing manufacturing processes.
  • Technology: Manufacturing is becoming increasingly technology-driven. Training equips employees with the skills to operate and maintain advanced machinery and systems.
  • Productivity: Engaged workers tend to be more productive, contributing to increased output and profitability for the manufacturing company.
  • Compliance: Manufacturing is subject to various regulations and industry standards. Training ensures that employees understand and comply with these requirements, avoiding legal and regulatory issues.

Effective training programs are designed to align with the organization’s goals and objectives, ensuring that the workforce is well-prepared and capable of contributing to the success of the manufacturing operations.

In summary, training in manufacturing is a subset of skills development, with a narrower and more specific focus on teaching job-related skills and knowledge. Skills development, on the other hand, is a more comprehensive and ongoing process that aims to develop a well-rounded and adaptable workforce capable of meeting the evolving challenges of the manufacturing industry. Both training and skills development are important for the success of a manufacturing organization, and they often complement each other in the development of a skilled and competent workforce.

How Can Technology Improve Manufacturing Skills Development and Training

Technology can significantly enhance manufacturing skills development and training by making the process more efficient, effective, and accessible. Incorporating these technological advancements into manufacturing skills development and training can lead to a more skilled and adaptable workforce, increased safety, reduced training costs, and improved overall manufacturing efficiency.

For example, technology enables experts to remotely assist and guide trainees through complex tasks. Workers can wear smart glasses or use mobile devices to share live video streams and receive real-time instructions. AI-driven connected worker solutions can assist in creating personalized learning paths for trainees based on the work they do, their progress, and their learning style.

Smart connected worker platforms, Learning Management Systems (LMS), and mobile apps can provide access to a wide range of training materials, including video tutorials, interactive modules, and assessments. These platforms allow workers to learn at their own pace and on their schedule, reducing the need for expensive and time-consuming in-person training.

Augmentir is the world’s leading, smart, connected worker solution using the foundational AI technologies underpinning ChatGPT to enhance manufacturing training, onboarding, and skills development. Leading manufacturing organizations are using our smart, connected worker suit and AI-driven insights to foster environments of continuous learning, and make skills development and training processes more personalized, accessible, and effective.

Schedule a live demo to learn why manufacturing leaders are choosing us to improve the training lifecycle with digital skills management tools, real-time insights, and more.


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Learn how manufacturers combat the manufacturing skilled labor shortage and close skills gaps with an Augmented Connected Workforce (ACWF).

An Augmented Connected Workforce (ACWF) offers manufacturing and other industrial organizations a powerful solution to combat the ever-worsening skilled labor shortage and skills gap. According to a report by Deloitte and the Manufacturing Institute, an estimated 2.1 million manufacturing jobs could go unfilled by 2030 and the cost of those missing jobs could potentially total $1 trillion in 2030 alone.

augmented connected workforce acwf manufacturing

By integrating advanced technologies like artificial intelligence (AI), connected worker platforms, and other emerging solutions manufacturers can enhance the capabilities of their existing workforce and bridge skill gaps. Connected worker tools offer real-time monitoring of your frontline workforce, ensuring seamless operations. Moreover, connectivity enables remote collaboration, allowing experts to assist frontline workers from anywhere in the world. This interconnected ecosystem empowers workers with the tools they need to succeed and attracts new talent by showcasing a commitment to innovation and technology-driven growth.

Through an ACWF, manufacturers can effectively combat the manufacturing skilled labor shortage and close the skills gap while driving productivity, innovation, and remaining competitive. Read more about ACWF in manufacturing below:

Implementing an ACWF in Manufacturing

A critical element of transitioning from a traditional workforce to an Augmented Connected Workforce (ACWF) is implementing and adopting new technologies and processes. Here are a few steps that can help with the adoption of ACWF technologies and smooth transitions in industrial settings:

  • Step 1: Assess Current Processes – Organizations must understand existing workflows and identify areas where AI, connected worker platforms, and other ACWF technology can replace paper-based and manual processes to enhance efficiency and productivity.
  • Step 2: Invest in Technology – Procure  AI-driven analytics platforms, mobile technology, and wearable technology to enable real-time data collection and remote collaboration.
  • Step 3: Training and Onboarding – Provide comprehensive training programs to familiarize workers with new technologies and workflows. Emphasize the importance of safety protocols and data privacy.
  • Step 4: Pilot Programs – Start with small-scale pilot programs to test the effectiveness of the implemented technologies in real-world manufacturing environments. Target high-value use cases that can benefit from a transition from paper to digital.
  • Step 5: Continuous Improvement – Gather feedback from workers and supervisors during pilot programs and adapt implementation initiatives based on their input. Continuously optimize processes and technologies for maximum effectiveness.

By following these steps, manufacturers can smooth the transition from a traditional manufacturing workforce to an ACWF, empowering their frontline workers with improved capabilities, skills, and overall operational excellence.

Supporting Learning in the Flow of Work

Augmented Connected Workforce (ACWF) technologies allow for increased frontline support and for new processes around learning and training to strategically upskill and reskill, reduce time to competency for new workers, and to combat the skilled labor shortage in manufacturing and more. Connected worker tools, such as wearable devices and IoT sensors, enable real-time monitoring of worker performance and environmental conditions, ensuring safety and efficiency on the factory floor.

pyramid of learning

An ACWF also allows for improved workflow learning capabilities giving frontline workers access to expert guidance, remote assistance and collaboration, microlearning, and other learning in the flow of work options regardless of the worker’s location.

ACWF tools further enhance frontline activities through:

  • Digital work instructions and guidance: Smart, connected worker platforms provide digital work instructions, procedures, and visual guidance easily accessible to workers on mobile devices.
  • Digital mentors and training: Some ACWFs incorporate “digital mentors” – GenAI-powered industrial assistants that can provide step-by-step guidance to workers, especially new hires.
  • Knowledge capture and sharing: Connected frontline worker applications capture data and insights from frontline workers, which can then be analyzed by AI software and used to improve processes, update work instructions, and share knowledge across the organization
  • Performance monitoring and feedback: ACWF solutions provide visibility into worker performance, allowing managers to identify areas where additional training or support is needed.

augmented connected workforce in manufacturing

In summary, ACWF initiatives empower frontline workers with the digital tools, knowledge, and support they need to learn and improve their skills directly within their daily workflows, rather than relying solely on formal training programs. This helps close skills gaps and drive continuous improvement.

Future-proofing Manufacturing Operations with an ACWF

Adopting an Augmented Connected Workforce (ACWF) approach centered around augmenting frontline workers with mobile technology, immersive training, collaborative decision-making, and continuous improvement, allows manufacturers to future-proof their operations and gain a sustainable competitive advantage. This concept empowers employees with powerful tools that augment and enhance their capabilities, productivity, and overall business processes by accessing critical information and fostering collaboration

AI-powered software can analyze vast amounts of data to optimize production processes and predict workforce development needs. At the same time, connected frontline worker solutions enable the integration of mobile and wearable technologies and provide real-time data insights, aiding in optimizing factory operations and adapting to evolving industry trends.

For an Augmented Connected Workforce, integrating AI and connected worker technologies serves as a vital strategy for manufacturers navigating the skilled labor crisis. Augmentir encourages organizations to embrace ACWF transformations and expedites adoption through a comprehensive connected worker platform leveraging the combined benefits of connected worker and AI technologies.

With Augmentir, frontline workers can access critical information, real-time data and insights, and expert advice and guidance all in the flow of work preventing lost time and improving both efficiency and productivity. Schedule a live demo to learn more about how an Augmented Connected Workforce future-proofs manufacturing operations and enhances frontline activities.


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Learn the differences between onboarding and training in manufacturing, their benefits, and how to improve them with continuous learning.

Onboarding and training are essential components of integrating new employees into a manufacturing environment. Research by Brandon Hall Group found that organizations with a strong onboarding process improve new hire retention by 82% and productivity by over 70%. Additionally, research from NAM and The Manufacturing Institute has found that manufacturing organizations invest an average of 51.4 hours per employee in training and are increasing overall investment in training by an average of 60% in response to the growing skilled labor crisis.

onboarding vs training in manufacturing

Onboarding and training are two key components of a skilled workforce that, while similar, serve different purposes and cover distinct aspects of the employment process.

Both processes are crucial, as onboarding ensures that employees understand the organization’s broader context, and training ensures that they have the expertise to contribute to the manufacturing processes and meet quality and safety standards.

A successful combination of effective onboarding and comprehensive training can lead to more engaged, skilled, and productive employees in the manufacturing industry. Unfortunately, according to Gallup, only 29% of new hires say they feel fully prepared and supported to excel in their role after their onboarding experience.

Read below to learn more about the differences between onboarding and training in manufacturing, why they are both critical to manufacturing success, the benefits of improving them, and how continuous learning strategies coupled with connected worker solutions can improve both and deliver impressive results.

Breakdown of Onboarding and Training Differences

Onboarding in manufacturing is about orienting new hires to the company as a whole, while training is about equipping them with the specific skills and knowledge needed to perform their job functions effectively. Below a breakdown of the differences between onboarding and training in a manufacturing setting:


  • Purpose: Onboarding integrates a new employee into the organization and its culture. It aims to familiarize employees with the company, its policies and procedures, and their roles within the organization.
  • Focus: Onboarding focuses on introducing employees to the broader aspects of the company, such as its mission, values, and culture, as well as administrative and safety procedures.
  • Duration: Onboarding is typically a short-term process, often lasting a few days, but could extend to a few months in certain manufacturing environments.
  • Components: It may include activities like completing paperwork, understanding company policies, meeting the team, plant/site safety, and familiarizing a new hire with the physical workplace.


  • Purpose: Training in manufacturing is a more specific and in-depth process that imparts the knowledge, skills, and competencies necessary to perform the job effectively. It is task-oriented and aimed at ensuring that employees can carry out their roles proficiently.
  • Focus: Training focuses on the technical aspects of the job, safety protocols, equipment operation, quality standards, and other job-specific skills.
  • Duration: Training is an ongoing process and may vary in duration depending on the complexity of the role and the employee’s experience level.
  • Components: Training tends to include hands-on instruction, demonstrations, practice exercises, and assessments to ensure that employees gain the necessary skills and knowledge.
Pro Tip

Both initial onboarding and ongoing training can be implemented with mobile learning solutions that leverage connected worker technology and AI to provide workers with bite-sized, on-demand training modules that they can access on smartphones or tablets. These modules can be developed with customized learning paths that are focused on the type of tasks and work employees are doing on the factory floor.


Why are training and onboarding important to manufacturing success

Onboarding and training are crucial to manufacturing success for several reasons including safety, compliance, quality, and more. A well-trained manufacturing workforce that has a deep understanding of company policies, its mission, and overall values drives successful initiatives by producing quality products, complying with both industry-wide and company-specific standards, and meeting production goals in a manner that is both safe and efficient.

The manufacturing industry is subject to numerous regulations related to safety, environmental practices, and product quality. Proper training ensures that employees are aware of and adhere to these regulations, reducing the risk of compliance violations and a well-structured onboarding program leads to lower turnover rates and a more effective and cohesive workforce, ultimately contributing to manufacturing success.

In summary, these two tools are essential in manufacturing for setting the stage for employee success and overall organizational success. Onboarding aligns new employees with the company’s culture, policies, and expectations, enhances their safety awareness, and fosters engagement and productivity, while training plays a pivotal role in contributing to manufacturing success by equipping employees with the knowledge, skills, and competencies necessary to perform their roles effectively.

What are the benefits of improving training and onboarding in manufacturing

Improving manufacturing employee onboarding and training offers several advantages, benefiting both the company and its employees. Comprehensive onboarding makes new hires feel connected to the company’s culture and values, while ongoing training can offer growth and development opportunities, leading to increased employee engagement and job satisfaction.

Companies with a skilled, well-trained workforce are more competitive in the marketplace, as they can produce higher-quality products at a lower cost and adapt to industry changes more effectively.

Training and development opportunities are often cited as a key factor in employee satisfaction. When employees feel that their skills are being enhanced and their careers are advancing, they are more likely to be satisfied with their jobs.

How continuous learning and connected worker solutions improve training and onboarding in manufacturing

Continuous learning and connected worker solutions can significantly enhance training and onboarding in manufacturing by providing more dynamic, effective, and adaptable approaches.

By incorporating continuous learning and connected worker solutions into the these processes, manufacturing companies can create more efficient, engaging, and rewarding experiences for employees. This not only accelerates the integration of new employees but also supports ongoing skill development and knowledge retention once on the job, ultimately improving productivity and the overall success of the organization.

connected worker as part of connected enterprise

Augmentir’s AI-based connected worker solution is being leveraged by manufacturing leaders to deliver continuous learning and development tools to optimize onboarding training for a rapidly changing and diverse workforce. Our innovative, smart connected worker suite is transforming how manufacturing organizations hire, onboard, train, and deliver on-the-job guidance and support.


digital skills management in a paperless factory

Schedule a live demo today to learn how our smart, connected worker solutions, AI-driven insights, and digital skills management are optimizing training and onboarding programs, tracking individual and team progress, and delivering targeted training and upskilling.


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Learn how to apply everboarding in manufacturing, and how it is replacing traditional onboarding and training methods.

According to Brandon Hall Group research, investment in employee training and development programs to enhance skills and knowledge is the highest-rated initiative globally to improve the employee experience. One highly effective approach towards revolutionizing training and onboarding is a continuous learning method called everboarding.

applying everboarding in manufacturing

Everboarding is a modernized approach toward employee onboarding and training that recognizes learning as a continuous and ongoing process. Its foundational characteristic is the belief that learning doesn’t stop after the initial onboarding period. Instead, everboarding emphasizes continuous skill development and employee knowledge enhancement throughout their careers.

Applying everboarding in a manufacturing environment involves tailoring continuous learning and development approaches to the unique needs and challenges of factory floor operations. As industrial processes evolve, employees must be routinely educated on process improvements, new technologies, safety standards, and efficiency initiatives.

Read on to learn more about how to apply everboarding to the factory floor and how fostering a culture of continuous improvement and learning keeps frontline workers safe, efficient, and engaged:

Steps for Implementing Everboarding in Manufacturing Operations

Everboarding in the context of the manufacturing industry refers to a forward-looking approach that ensures employees remain well-trained, adaptable, and aligned with industry standards throughout their tenure. This is essential in dynamic and fast-paced industrial environments like manufacturing. Here are some steps and strategies to begin implementing everboarding in your operations:

  1. Operationalize Learning: Develop and maintain a systematic approach to training and workforce development and ensure that ongoing training and development are available for all shop floor workers.
  2. Develop Learning Pathways: Create clear learning pathways and career development plans for employees. These pathways should outline the skills and knowledge required for career advancement within the manufacturing shop floor.
  3. Implement Digital Learning Platforms: Leverage digital learning platforms and smart, connected solutions to provide employees with access to training materials, videos, courses, and other resources. These platforms can track progress, and employees can learn at their own pace.
  4. Integrate Learning into the Workflow: Using digital, mobile, and connected technologies, organizations can integrate training into the factory floor for moment-of-need guidance and microlearning that allows frontline workers to stay compliant and operations to continue smoothly.
  5. Provide Feedback and Improvement Loops: Create a feedback mechanism where employees can provide suggestions for improving training programs and processes. Make sure to act on the feedback to continuously enhance the training experience.
  6. Initiate Regular Skill Assessments: Implement regular assessments and evaluations to identify areas where employees need further training or improvement.

Everboarding in a manufacturing factory floor environment is critical for keeping the workforce skilled, adaptable, and able to meet changing demands and technological advancements. By fostering a culture of continuous learning and improvement, you can ensure that the factory floor remains efficient and productive.

5 Useful Everboarding Technologies

Implementing Everboarding in manufacturing requires the use of various technologies to facilitate continuous learning and skill development. Here are five (5) useful technologies that can help speed the adoption of everboarding methods on the factory floor and support frontline workers on their continuous learning paths.

  1. Learning Management Systems (LMS): LMS platforms are essential for delivering and managing training content. They allow manufacturing companies to organize courses, track employee progress, and ensure compliance with training requirements.
  2. Connected Worker Applications: Connected worker applications provide mobile solutions, real-time data, and actionable insights that enable customized and personalized training dedicated to the needs of individual workers and specific tasks.
  3. Artificial Intelligence (AI): AI-driven systems can personalize training content based on employee performance and preferences. AI’s ability to process vast amounts of data, provide personalized experiences, and offer real-time feedback makes it a powerful tool for implementing everboarding.
  4. Internet of Things (IoT): IoT sensors can be integrated into manufacturing equipment to gather data on machine performance and employee interactions. This data can inform training needs and help identify areas for improvement.
  5. Wearable Technology: Wearable devices can be used for on-the-job training and performance monitoring. They are especially useful in high-risk manufacturing environments.

These technologies leverage connectivity, digital tools, and data to create a more dynamic and adaptive learning environment for frontline employees. By integrating emerging technologies like smart, connected worker solutions into manufacturing operations, companies can create a more agile and adaptive learning environment that supports the foundations of everboarding.

Pro Tip

Digital training tools can help implement everboarding and improve learning speed and retention. For example, workers who need visuals or real-world scenarios can access them using AI-powered software to create a comprehensive everboarding and training program that supports frontline employees throughout the entire skills and training lifecycle.


Improving Manufacturing Training with Everboarding

Implementing new learning technologies in any industry is met with a certain number of challenges. This remains especially true for the factory floor where training and development are traditionally separate from the work being done, and where traditional onboarding has been a one-and-done type of approach.

However, because everboarding is a process of continuous learning, organizations can improve their industrial training and onboarding, ensuring employees continually acquire new skills and knowledge to adapt to evolving technologies and processes. This not only helps in training new employees but also enables continuous learning and skill development for the entire workforce, improving productivity, safety, and quality in the process.

Implementing everboarding in factory floor operations can seem complex but it is a rewarding process that can be streamlined through solutions like Augmentir’s connected worker solution. With our AI-driven insights, our connected solution reduces onboarding time and transforms workforce training, bringing learning to the factory floor through intelligent guidance that delivers information to workers at the point of need.

Learn how manufacturers are implementing Augmentir’s AI-driven connected worker tools to capture and digitize tribal knowledge, reskill and upskill their workers, and empower their frontline teams – schedule a live demo today.


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The evolution of connected worker software, how industrial transformation leaders are meeting modern challenges with a generation of tools.

Beginning in mid-2022 and now increasing in 2023, there is a significant trend of companies moving away from earlier investments in connected worker software tools to Augmentir’s Connected Worker Platform.

Early adopters and pioneers of V1.0 connected worker tools and technology deserve respect for leading the charge into Industry 4.0 and the concept of a connected workforce. However, we also admire those leaders who realized there are more transformations and improvements to make – such as value in the data from your connected workers and incorporating AI-driven solutions to make sense of that data. These innovative leaders dared to adapt, continue innovating, and replace the connected worker software systems that were not solving enough of the challenges faced by the modern workplace.

darwin in manufacturing

By combining AI-powered software and smart connected worker solutions, manufacturers are able to get next-level results and improve frontline worker productivity, engagement, and safety.

Following in the Footsteps of Industrial Transformation Leaders

According to LNS Research (a leading analyst firm in defining the connected worker space), the business case for connected worker software continues to grow, and solutions that incorporate emerging technologies like AI are leading the way. In fact, LNS states that Industrial Transformation Leaders (IX Leaders) are two times more likely to use AI-enabled advanced analytics capabilities. These leading manufacturers are supporting their frontline operations with AI-based technology for training and skills development, real-time worker performance support, and providing dynamic and personalized content.

Here at Augmentir, we have seen quite a few companies that fall into the category of the courageous, understanding that they needed to continue adapting for their business to thrive.

We have been honored to be recently chosen by several global leaders as their connected worker V2.0 solution, including:

  • one of the largest paint manufacturers in the world
  • one of the largest agricultural companies in the world
  • one of the largest food manufacturers in the world
  • one of the largest manufacturers of batteries in the world

All of these world leaders recognized that their current connected worker software solutions had become insufficient and that they needed a smarter, more complete solution to help them overcome their frontline workforce challenges and current business obstacles.

Here are three key takeaways you can use from these companies that went back to select a new connected worker solution:

  1. Don’t be afraid to make a change that will have a positive impact on your business, even if you are the one who made the initial decision.
  2. If you have experience choosing early connected worker tools, build on that experience. You are ideally situated to identify gaps in processes and improvement needs; and know best which tools to use to address the overall operational needs of the business.
  3. Use your prior experiences to build processes for re-evaluating connected worker solutions from the perspective of already experiencing one fully deployed.

In one example, a global manufacturer invested in an early connected work tool and had been using the tech for nearly 4 years. However, once they decided they needed a new solution, they then went back to evaluate the market for the right tool. They made a list of selection criteria they knew they wanted from this new solution, from that they looked at approximately fifteen (15) connected worker vendors, and from there they narrowed down to the three (3) they ended up testing. They even included having a couple of integrations in their POC as they knew that an integration into their ERP, Quality Management, and Asset Management systems was something they needed, and they had poor experiences previously with vendors overcommitting.

Pro Tip

We suggest anyone evaluating a technology use this same approach – include integrations as part of your Proof-of-Concept to ensure that you are not getting hypothetical answers to hypothetical questions, and that the solution meets your true business needs.

What our customers tell us

Here is what customers are telling us they are looking for in a V2.0 connected worker solution, and the reasons they changed to Augmentir’s Connected Worker Platform:

  1. Ease of Use: Augmentir prioritizes a user-friendly experience. Its intuitive interface and workflow builder makes it easy for employees to adopt and use the tool effectively. This can result in faster onboarding and increased overall productivity.
  2. Augmented, Personalized Work Instructions: Augmentir provides a workflow and content creation environment that allows you to digitize standardized work instructions, and adjust content and in-line training to suit the needs of individual workers.  This optimizes performance and speeds up onboarding time for new employees.
  3. Upskilling and Reskilling: Augmentir’s ability to deliver formal skills and learning in the flow of work means a worker can stay current in their needs, continue to grow in their role, and build a structured career path within their company. This approach appears to be driving increased retention and job satisfaction.
  4. Workforce Optimization: Augmentir’s ability to assess in real time who is available to work on any given day and then balance the skill level best suited for a task with the available workforce offers optimal productivity based upon what you have to work with on any given day.
  5. Digitizing Complex Workflows: Most solutions on the market allow you to digitize simple workflows. With Augmentir, manufacturers can build complex workflows that satisfy use cases that are unique to their business, and extend those workflows to support greater integration into their business processes.
  6. Industrial Collaboration: Augmentir enables remote collaboration among workers and experts. This functionality is particularly useful when experts are not physically present at the job site. Remote experts can guide workers through AR annotations and audio/video communication, fostering knowledge sharing and faster problem resolution.
  7. Continuous Improvement: Augmentir focuses on driving continuous improvement within organizations. It leverages AI to analyze data from worker interactions and identifies areas for improvement. This data-driven approach allows companies to optimize processes, increase productivity, and reduce costs over time.
  8. Integration and Scalability: Augmentir offers integration capabilities with existing enterprise systems, such as enterprise resource planning (ERP) or manufacturing execution systems (MES). This ensures seamless data exchange and workflow integration. Additionally, Augmentir is designed to scale with the organization’s needs, accommodating both small teams and large enterprises.
  9. Analytics and Insights: Augmentir provides robust analytics and reporting features driven by AI-powered solutions and focuses on AI as a core component of Connected Worker V2.0. This allows managers and supervisors to gain valuable insights into worker performance, task completion times, and areas that may require additional training or support. Data-driven analytics can aid in identifying bottlenecks, optimizing processes, and making informed business decisions.
  10. Customization and Flexibility: Augmentir allows organizations to customize their work instructions and workflows to fit their specific needs. This flexibility enables the tool to adapt to different industries, processes, and work environments.


If you are interested in learning for yourself why companies are choosing to change to Augmentir over their current connected worker solution – reach out to book a demo.


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A connected worker strategy is critical to the success of your connected enterprise and digital transformation initiatives.

In today’s always-changing industrial landscape, organizations are acutely aware that adopting innovative technologies and processes is not just a “nice-to-have” but a “must” to stay competitive. According to PwC, 75% of manufacturers believe that Connected Enterprise technologies will have a major impact on their business over the next five years. By 2025, the number of connected devices in industrial settings is expected to reach 21.5 billion, making it clear that the adoption of connected technologies is a critical step for any organization that wants to succeed in the future.

connected enterprise

However, there is one aspect of a truly connected enterprise that many manufacturers overlook – their frontline workforce.

Frontline workers play a critical role in ensuring the safety, quality, and uptime of production operations, yet too often these workers are disconnected from the rest of the business. Connected frontline worker (CFW), refers to the use of technology to connect workers with the digital systems and processes in their organization, making it easier for them to collaborate, access information, and perform their jobs more efficiently. To fully realize the benefits of a connected workforce, it is essential to understand how they fit into the larger Connected Enterprise concept.

Learn more about what a connected enterprise is and the role that connected worker solutions play in the following sections:

What is a connected enterprise?

Connected Enterprise refers to the integration of digital technologies, data, and analytics across an organization’s entire operational landscape to improve efficiency, productivity, and profitability. Companies are rapidly adopting advanced technologies to improve their business operations. This concept spans several initiatives within an organization: assets and equipment, the products being manufactured, the end customer, operations, workers, and the entire supply chain.

connected enterprise - LNS Research

Source: LNS Research

Connected worker (or connected frontline worker – CFW) technology is a crucial part of this concept – as it connects the human workforce with the digital systems and processes in the organization.

How to create a connected enterprise

The first step to creating a connected enterprise is implementing smart, connected worker solutions. AI and connected frontline worker technologies are some of the leading solutions organizations are turning to on their path toward a Connected Enterprise. Augmentir has seen manufacturers achieve significant results after successfully implementing connected frontline worker solutions in conjunction with AI-driven analytics:

  • Up to a 72% reduction in training and onboarding times
  • More than 20% decrease in downtime
  • Nearly a 25% increase in productivity

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 for an organization’s connected enterprise initiative. Data from actual work performance combined with AI-based analytics can inform workforce development investments, and deliver smart insights that reduce time to productivity, enable targeted reskilling and upskilling, and provide individualized guidance and support at the point of work so that you get the best each person has to offer.

connected worker as part of connected enterprise

However, companies need to be strategic and take a structured approach. It is imperative that the right solutions are identified and tested by the right divisions, personnel, and business units.

LNS Research has developed an “Industrial Transformation Reference Architecture” approach that provides a framework and simplifies implementation into four layers:

  1. Business Processes and Systems
  2. Connected Assets and Operations
  3. Data and Analytics
  4. Connected Worker

These guidelines give organizations reference points to help guide them along their path of industrial transformation and set them up for success in connecting their operations.

Key benefits of connecting your workforce to your enterprise

By leveraging AI and other smart technologies, companies are providing workers with real-time guidance and assistance, enabling them to perform their jobs more effectively. Frontline workers can access information, collaborate with colleagues, and receive real-time alerts on potential hazards, all of which help to improve their productivity and safety.

The benefits offered by AI and connected technologies are significant:

  • Improved efficiency: By automating routine tasks and providing real-time information, AI and connected worker technologies can help streamline operations and reduce errors.
  • Increased productivity: AI and connected worker technologies can help workers perform their jobs more effectively, enabling them to produce more goods in less time.
  • Better quality control: By providing real-time data on production processes and product quality, AI and connected worker technologies can help identify issues early and prevent defects.
  • Enhanced safety: Connected worker technologies can provide workers with real-time guidance and assistance, enabling them to perform their jobs more safely and avoid accidents.
  • Cost savings: By reducing downtime, improving efficiency, and enhancing product quality, connected worker technologies can help companies save money and increase profitability.
  • Improved decision-making: By providing real-time insights and data analytics, connected worker technologies can help companies make more informed decisions about their operations and identify new opportunities for growth.

According to McKinsey & Company, by 2030, the adoption of “Connected Enterprise” technologies is expected to generate $1-2 trillion in value for the global economy, including the manufacturing industry. As the transformation from paper processes to digital continues, industrial organizations are consistently finding that CFW solutions are an essential component of a larger “Connected Enterprise”. By leveraging AI and other advanced technologies to better analyze data and provide actionable insights, companies empower workers with the tools to perform their jobs more effectively, improving productivity, efficiency, and safety. Adopting AI and connected worker technologies is a key part of industrial transformation and of “Connected Enterprise” initiatives, offering industrial organizations an enhanced competitive advantage and solutions to many of the obstacles they face in today’s markets.

Implementing a connected enterprise with Augmentir

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Learn how to digitize quality assurance, its benefits, and how digital inspection procedures reduce errors in manufacturing.

Quality assurance (QA) and inspection procedures work hand in hand to ensure customers receive quality products free of deficiencies. But what do the terms mean exactly?

QA is a systematic process that manufacturers use to ensure that a product or service meets the requirements for distribution. QA inspections are a subset of that process, checking products before they go off the line. Inspections are a crucial part in troubleshooting and fixing product defects, making improvements, and maintaining compliance. 

standardize digitize quality assurance manufacturing

These inspection procedures should be standardized and digitized to create a quality assurance system that ensures workers have access to the correct procedures and that tasks are performed in a standard manner to avoid errors on the production floor. This results in reduced defects, optimizes quality data collection, and decreases the need for rework.

Explore the following topics to learn how to decrease mistakes on the shop floor when you digitize and standardize quality assurance procedures:

Standardization and digitization explained

Standardization and digitization work in tandem. Let’s break down the two concepts to get a better idea of how they work.

Standardizing means developing a set of rules for how tasks should be completed. It boils down to this: When you standardize tasks, you’re giving your employees an established, time-tested process to use.

When done right, standardization decreases ambiguity, enhances productivity, boosts quality, and increases worker morale.

Digitization, on the other hand, involves converting information into a digital format. Keep in mind that it’s the information you are digitizing, not the processes or procedures. Automating your work processes using a single system, like a connected worker platform, makes everyday operations much faster and easier to accomplish. Enhancing this further with AI-driven analytics and process optimization empowers manufacturers and frontline personnel with the right tools for quality data collection and inspection procedures.


standardize and digitize quality assurance procedures

How standardizing QA and inspection procedures reduces errors

According to LNS Research, to digitize quality assurance processes, manufacturing leaders must leverage emerging technologies. This allows them to achieve step-change improvements across operations. When you standardize quality assurance procedures, you’re ensuring processes are completed using best practices and proven methods.

Think of it this way: When workers complete tasks using their own choice of tools, platforms, or reporting mechanisms, it’s harder to measure and evaluate which procedures are bringing value and which ones are not. It also leaves a lot of room for human error and inefficiency.

QA and inspection procedures should be standardized so that a worker’s way of doing things aligns with the company’s overarching objectives. If you don’t standardize inspection procedures, you’ll have a more difficult time pinpointing product deficiencies and worker errors.

Smart, connected worker platforms and AI-based software allow manufacturers to standardize processes across all units, creating a single source of truth for a truly optimized procedure that can be audited and verified, resulting in fewer errors, reduced defects, and more expedited inspections overall. Every procedure, regardless of how often it’s performed, can have guidelines that define the scope and methods for how to perform it. This in turn ensures a higher quality result every time.

How digitizing quality assurance procedures minimizes mistakes

Converting your paper-based QA procedures to a digital format is one of the smartest things a manufacturer can do. From there, you can set up a unified system to improve QA assurance processes.

Workers are only human, and quality assurance systems safeguard the production process. It identifies mistakes as they happen and uses communication tools to reduce the risk of error. Other strategies such as a “first time quality” (FTQ) or first time right plan enhance standards, practices, and resources to ensure all processes on the production floor are performed correctly the first time.

Deploying an integrated system makes it easier to:

  • Gradually improve your production processes
  • Standardize your QA methods
  • Digitize manufacturing processes


Connectivity and connected worker technology empowers all workers to do their jobs better and in a timelier manner. It also gives managers the opportunity to track how well employees are carrying out standardized QA procedures and inspections. When coupled with AI-driven analytics that can process the massive amounts of data connected workers generate, manufacturers are able to derive better insights, faster, and with higher reliability. This essentially transforms frontline workers into quality assurance sensors that further enhance and empower quality inspections.

If you’re still using paper checklists to track procedures, you’ll never see beyond what’s in front of you. By digitizing analog paper practices you are enabling better quality data collection and inspection procedures and strengthening your overall manufacturing operations. 

Thankfully, Augmentir’s connected worker solution gives real-time visibility into all operational processes, from anywhere. Industrial companies use our breakthrough system to standardize and digitize quality assurance procedures.



If you are interested in learning for yourself why companies are choosing Augmentir to help standardize and digitize their quality assurance procedures – reach out to book a demo.


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Learn about autonomous and preventive maintenance, and how they can maximize machine efficiency and worker productivity on the shop floor.

Autonomous and preventive maintenance are two manufacturing strategies for maintaining machinery on the shop floor. The main difference between the two is that autonomous maintenance (AM) places greater responsibility for equipment upkeep on operators, while preventive maintenance (PM) is carried out by maintenance workers. Both autonomous and preventative maintenance strategies benefit from smart, connected worker technologies, although in different ways.

autonomous vs preventive maintenance

AM, for example, focuses on training machine operators to be the point of reference for cleaning, inspecting, and making minor repairs on the spot. This approach aims to empower operators to take the initiative in monitoring their equipment and identifying issues early on. By introducing smart, connected worker technology, like Augmentir’s suite of connected worker tools and closed-loop autonomous maintenance solution, manufacturing leaders can give operators more control over inspections and help intelligently guide and support operators, resulting in minimized machine downtime.

PM, on the other hand, consists of scheduling regular maintenance activities like part replacement, lubrication, and calibration. Workers tasked with PM ensure equipment remains in tip-top condition, which helps to prevent future breakdowns. The goals of this strategy are to avoid machine downtime and reduce the need for unplanned repairs. Smart, connected worker solutions improve the quality, transparency, and efficiency of both autonomous and preventive maintenance and repair procedures by standardizing and optimizing maintenance procedures.

You can learn more about autonomous and preventive maintenance by exploring the following sections:

What’s autonomous maintenance and its advantages?

Autonomous maintenance involves machine operators tackling basic equipment upkeep tasks to ensure that everything runs smoothly on the production floor.

When implemented, AM can yield a number of benefits:

  • Reduced equipment downtime: Conducting routine upkeep activities can prevent breakdowns and limit the need for unplanned maintenance.
  • Greater machine reliability: Operators who are trained to maintain their own equipment are more likely to pinpoint problems before they lead to machine failure.
  • Prolonged lifespan of machinery: Equipment that is maintained will last longer and require fewer repairs or replacements.
  • More operator involvement: Operators who take an active role in preserving their machinery feel empowered.
  • Increased safety: It’s easier to troubleshoot potential hazards before they turn into accidents when operators frequently inspect and maintain their equipment.
  • Cost-effectiveness: Reducing unplanned maintenance can save manufacturers significant money over time.

When coupled with smart, connected worker technology and AI-driven analytics, AM’s benefits are further enhanced. Digitizing autonomous maintenance processes increases standard work adherence, clears defects faster, and improves auditability. Connected worker technology enables operators to share knowledge and gives them access to the resources they need right when they need them.

autonomous maintenance


What’s preventive maintenance and its benefits?

Preventive maintenance focuses on performing routine equipment upkeep tasks at scheduled intervals. The goal is to avert equipment failure and limit unplanned downtime or repairs.

The benefits of having dedicated workers perform preventive maintenance are:

  • Enhanced machine reliability: Regular maintenance increases the odds of identifying and fixing problems before they turn into mechanical failures.
  • Decreased downtime: Conducting routine upkeep at scheduled times can decrease unplanned maintenance and increase production efficiency.
  • Greater compliance: PM can help manufacturers better comply with regulatory requirements to prevent unnecessary penalties for non-compliance.
  • Better planning protocols: Recruiting specialized maintenance personnel with extensive training on machine upkeep and repair can lead to better planning and allocation of resources.
  • Increased safety: Training workers on basic maintenance techniques ensures that deficiencies are addressed in a timely manner to avoid any injury.

PM’s impact is improved when used alongside smart, connected worker solutions that allow for digital work instructions and remote collaboration to effectively and efficiently guide technicians. Additionally, by digitizing and automating maintenance notifications, organizations can improve communications, speed up maintenance procedures, and minimize machine downtime.

How to implement AM

Applying autonomous maintenance to everyday maintenance tasks can mitigate potential machine disasters. Organizations can take this even further by creating “smart” autonomous maintenance processes and implementing advanced connected worker solutions with AI-driven insights. This gives operators improved control over maintenence process and expert guidence through a searchable asset hierarchy, maintenance history, and troubleshooting database.

The seven steps of effective AM implementation:

  • Boost operator expertise: It’s important to train operators on the machines themselves and how to perform maintenance tasks. This type of training can be made more effective through AI-based insights that integrate skills management into the flow of work and identify workforce development opportunities for upskilling and reskilling.
  • Conduct initial cleaning, inspection, and repairs: Operators should execute regular maintenance activities to avoid unplanned downtime. Furthermore, with connected worker solutions, operators can use mobile devices to digitally track and manage issues and activities as well as automate maintenance notifications further reducing overall downtime and avoiding unplanned downtime.
  • Eliminate causes of contamination: Routine cleaning and inspection minimize sources of contamination such as improper calibration and defective equipment. This alone can help prevent unexpected machine breakdowns. By building smart workflows into the autonomous maintenance process, manufacturers can schedule and assign standard work procedures (such as routine cleaning and calibration) digitally that have built-in work reporting for better visualization and auditing.
  • Define standards for cleaning, lubricating, and inspecting: Nailing down how to clean, lubricate, tighten and inspect, and how often to perform these upkeep duties, can help keep equipment in pristine condition. Smart digitization can standardize these practices across all manufacturing operations, giving organizations a global best practices standard to measure standard work adherence, clear defects more quickly, and improve auditability.
  • Perform inspection and monitoring: Operators who are trained on maintenance processes can carry out maintenance tasks independently and without error. With smart skills management and AI-enhanced workforce development, organizations can reduce training time and provide individualized guidance and support to workers when and where needed.
  • Standardize visual maintenance: Incorporate visual aids that help operators better understand equipment and labeling. For example, written procedures could contain a diagram showing how fluids should flow in a particular machine. Continuous learning and personalized insights via connected worker solutions are able to take this one step further and integrate things like instructional videos, interactive diagrams, and even remote experts into the flow of work to improve operational excellence and productivity.
  • Work towards continuous improvement: It’s imperative to strive for continuous improvement in maintaining machinery. Operators who are constantly learning and evolving are more productive and empowered with better decision-making capabilities through actionable, AI-driven insights.

Learn more on how to implement autonomous maintenance and the seven steps involved, or get in touch with us for a personalized demo to see Augmentir’s Autonomous Maintenance solution in action.

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How to implement PM

According to Forbes, when implemented correctly, preventive maintenance ensures that upkeep is performed at a set time to prevent unexpected machine deficiencies. Smart, connected frontline worker solutions are able to improve preventative maintenance procedures through smart communication, scheduled notifications and improved collaboration.

Eight steps for implementing preventive maintenance:

  • Establish project scope: Gauge which machinery will be inspected and which maintenance tasks are needed to be done at specific intervals.
  • Pinpoint upkeep requirements: Set requirements for which tasks are crucial for each piece of equipment. Tasks could vary from lubrication and calibration to inspections and part replacements.
  • Create maintenance schedule: Create a set schedule for carrying out PM tasks that’s based on equipment requirements, production schedules, and planned downtime.
  • Allocate worker responsibilities: Assign which tasks each maintenance worker is expected to fulfill.
  • Provide necessary resources: Give staff the proper tools, equipment, and supplies to execute PM tasks (e.g., lubricants, replacement parts, testing equipment, etc.).
  • Define metrics: Establish metrics for gauging the efficiency of PM (e.g., downtime, equipment reliability, maintenance costs, etc.).
  • Create training programs: Hands-on training and how-to instructions can help maintenance workers better understand how to perform upkeep tasks.
  • Monitor performance and adjust: Measure how well your PM efforts are doing and revise if necessary. This may mean updating procedures, adjusting maintenance schedules, or creating more training opportunities.

All of these steps are able to be standardized and optimized through connected worker solutions. Augmentir’s suite of connected worker tools delivers in-line training and support at the point of work, provides a searchable database to allow workers access to knowledge when and where needed, gives workers individualized guidance and support, connects teams for better collaboration, and more. This approach helps standardize and optimize maintenance processes and notifications as well as training, offering a better, more efficient adoption process for both frontline workers and management from start to finish, and giving everyone the proper tools for successful manufacturing operations.


If you are interested in learning for yourself why companies are choosing Augmentir to help digitize and optimize their autonomous and preventive maintenance programs – reach out to book a demo.


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