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AI Manufacturing 2021 – Event Recap

After more than a year of virtual conferences, we were finally able to participate in person at the AI Manufacturing conference in Dallas early this November and discuss how AI is shaping the future of the manufacturing workforce.

After more than a year of virtual conferences, we were finally able to participate in person at the AI Manufacturing conference in Dallas early this November. This year’s event was hybrid, face-to-face on November 3 and 4th, and virtually on November 5th. While it was refreshing to be able to network face to face with leaders in the Manufacturing industry, it was great to have the opportunity to also network virtually on November 5th. If you aren’t familiar with the AI Manufacturing conference, this conference is the leading Artificial Intelligence event for Manufacturing Industries. This year’s event focused on:

  • The use of AI to Improve Quality, Reduce Defects, and Increase Profits
  • Developing a Digital Twin to Optimize Plant Operations
  • Using Building Blocks to Modernize Manufacturing Activities and Facilitate Growth
  • Designing  Products Enabled by Additive and Hybrid Manufacturing Techniques
  • Exploring the Use of AI in Industrial Attacks and Defense

Using AI to Unlock the True Potential of Today’s Modern, Connected Workforce

Dave Landreth, Augmentir’s Head of Customer Strategy had the opportunity to present on “Using AI to Unlock to the True Potential of Today’s Connected Workforce”. In this session, he discussed the variability of the workforce with generations, how they need to be trained differently, and how AI can assist in worker proficiency. Dave also discussed Bob Mosher’s 5 moments of need and how AI can be applied at the time of learning. 

The Misunderstood Fear of AI

Our founders saw that the humanistic approach was missing with traditional connected worker platforms and realized that AI was the key to saving the manufacturing world and unlocking worker potential. However, companies are reluctant to adopt AI in fear that automation will take over and eventually replace human workers in manufacturing. Others fear that AI would be used negatively to track workers, in a “big brother” type of way.  

As we’ve seen with our customers, this couldn’t be farther from the truth. When AI is leveraged ethically with the workforce in mind, it can be used to help improve and ultimately grow the talent of your workers. Assessing workers on their performance has been done for years through subjective performance reviews. Using AI allows the assessments to be based on data and can provide a path forward for worker improvement and continued growth. 

Understanding Today’s Struggles Within Manufacturing

Manufacturing workforce challenges

The struggles that manufacturers face today aren’t the same struggles that were present 40 years ago. One of the number one issues in manufacturing is hiring. Today, most manufacturers believe that hiring is a risk, with a limited pool of candidates. They are struggling with employees who don’t have the needed skill set and are questioning how they can train them and evaluate their performance. 

Manufacturing companies also struggle with retaining employees. We are all aware of the workforce retention issues right now. Employees are feeling like they aren’t heard and that they can’t contribute to the company, which causes them to look for a new career. There is also the struggle of thoughtful upskilling, meaning that formal training programs only recognize one type of worker. The average manufacturing plant sees 4 generations of workers, ranging from those fresh out of high school to the ones that have worked on a plant floor for 40+ years. Different generations learn differently and require different levels of support. There isn’t a one size fits all approach for teaching different generations. 

Another challenge with the workforce that isn’t as obvious, is with mergers and acquisitions. An acquisition means that companies now consist of two workforces doing things differently and needing to understand what part of procedures from the newly acquired company is worth incorporating into the existing procedures.

Leveraging AI to Help Build and Grow a Top Performing Workforce

Build and grow a top performing manufacturing workforce

AI is uniquely suited to solve these challenges, and we recognized that early on at Augmentir. We started looking at how AI could help build and grow a top performing workforce. One way AI can help is the ability to hire for potential by increasing the hiring of candidates to those not as skilled. AI allows companies to understand a worker’s skillset and provides the ability for personalized workflows to guide them in the context of work while they are doing their job, whether it’s a new worker or one with dozens of years of experience. AI can also help with the “Right person – Right Job – Right Time” approach – always ensuring that the correct person is performing the task at the most efficient time. 

The use of AI allows all workers to contribute by allowing inline feedback to optimize work procedures. In addition, AI can be used to ensure personalized career job competency allows workers to be hired even if they do not have the optimal set of skills and experience. Measuring a worker’s proficiency when they are completing the work allows the worker to focus on each specific step and guides them at the time of need, instead of during classroom training. AI provides workers with predictive and stable data to help them grow in their roles. Having a data-driven way to measure success and provide advancement opportunities helps establish career paths as well as opportunities to grow. 

With an AI-based onboarding approach, organizations are able to hire a wider range of individuals with varying skill sets. If we can teach someone in the context of doing their work, onboarding time is reduced due to being able to train them in the field. We also see an increase in productivity and are constantly evolving their learnings. When workers feel included and confident about their careers, they are also more likely to want to stay and grow with the company. The ability to train workers in the field while doing their jobs with AI personalization allows you to clearly and quickly assess how a worker is doing, where you focus the help to them, and driving those 1:1 work procedures is a game-changer.

AI in Manufacturing will solve many of the challenges that we are seeing. 

Learning & Development and the 5 Moments of Need

The Five Moments of Need methodology was created by Bob Mosher, a thought leader in learning and development with over 30 years of experience. He realized that after 20 years, classroom teaching was the wrong approach since it rarely teaches you things that you do in your job on the shop floor. Classroom learning allows an individual to gain a certain level of confidence, but quickly falls off when it’s time to apply it within context to a given workflow.  

According to Bob’s methodology, the 5 moments when our workforce needs knowledge and information consists of: 

  • When people are learning how to do something for the first time (New).
  • When people are expanding the breadth and depth of what they have learned (More).
  • When they need to act upon what they have learned, which includes planning what they will do, remembering what they may have forgotten, or adapting their performance to a unique situation (Apply).
  • When problems arise, or things break or don’t work the way they were intended (Solve).
  • When people need to learn a new way of doing something, which requires them to change skills that are deeply ingrained in their performance practices (Change).

The approach that Bob and his team adopted in the last 10 years is to think more about performance support. The variability of the workforce, both skilled and young, proves that there’s not a one size fits all approach. This is where AI comes in: being able to deliver personalized work procedures for every worker, allowing for continuous learning and growth. Based on proficiency, there may be a more guided set of work instructions, a session with a remote expert, or a supervisor sign-off required in order to complete the job on quality and on schedule. AI can also be used to continuously measure and assess how the workers are doing. This is where organizations can start seeing growth within their workforce.

Looking Ahead

We had a blast at this year’s AI Manufacturing conference and are already looking forward to another successful event next year! If you’re interested in learning more about why AI is an essential tool in digital transformation, from reducing costs and downtime to improving over quality and productivity, we’d highly suggest considering attending next year. In the meantime, if you’re looking for information surrounding AI, digital transformation, and building a connected workforce, check out our eBook: “Building a Modern, Connected Workforce with AI”.

The Great Resignation in Manufacturing

Recently, Augmentir completed a rigorous qualification audit as part of a Tier 1 Pharmaceutical Manufacturing company’s Good Manufacturing Practice (GMP), and we are pleased to announce that our product successfully passed the audit.

A recent article published by The Washington Post shows some shocking numbers on the amount of Americans leaving their jobs over the past year. It’s no surprise that hotel and restaurant workers are resigning in high numbers due to the pandemic, but what is surprising is the fact that the manufacturing industry has been hit the hardest with “a nearly 60 percent jump” compared to pre-pandemic numbers. This “Great Resignation in Manufacturing” is the most of any industry, including hospitality, retail, and restaurants, which have seen about a 30% jump in resignations.

However, if you dig deeper, this trend isn’t new. This recent increase in job quitting in manufacturing has simply magnified a problem that had already been brewing for years, even prior to the start of the pandemic. In fact, in the four years prior to the pandemic (2015-2019), the average tenure rate in manufacture had decreased by 20% (US Bureau of Labor Statistics).

This accelerating workforce crisis is placing increased pressure on manufacturers and creating significant operational problems. The sector that was already stressed with a tight labor market, rapidly retiring baby-boomer generation, and the growing skills gap is now facing an increasingly unpredictable and diverse workforce. The variability in the workforce is making it difficult, if not impossible to meet safety and quality standards, or productivity goals. 

Manufacturing leaders’ new normal consists of shorter tenures, an unpredictable workforce, and the struggle to fill an unprecedented number of jobs. These leaders in the manufacturing sector are facing this reality and looking for ways to adjust to their new normal of building a flexible, safe and appealing workforce. As a result, managers are being forced to rethink traditional onboarding and training processes.  In fact, the entire “Hire to Retire” process needs to be re-imagined. It’s not the same workforce that our grandfather’s experienced, and it’s time for a change.

The Augmented, Flexible Workforce of the Future

The reality is that this problem is not going away. The Great Resignation in manufacturing has created a permanent shift, and manufacturers must begin to think about adapting their hiring, onboarding, and training processes to support the future workforce in manufacturing – an Augmented, Flexible Workforce.

What does this mean?

  • It means adopting new software tools to support a more efficient “hire to retire” process to enable companies to operate in a more flexible and resilient manner.
  • It means starting to understand your workforce at an individual level and using data to intelligently closes skills gaps at the moment of need and enables autonomous work.
  • And it means taking advantage of data.  More specifically, real-time workforce intelligence that can provide insights into training, guidance, and support needs.

Investing in AI-powered connected worker technology is one way to boost this operational resiliency. Many manufacturing companies are using digital Connected Worker technology and AI to transform 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 AI tools can gain insights into areas where the largest improvement opportunities exist. Artificial Intelligence lays a data-driven foundation for continuous improvement in the areas of performance support, training, and workforce development, setting the stage to address the needs of today’s constantly changing workforce. Today’s workers embrace change and expect technology, support and modern tools to help them do their jobs.

 

To learn more about how AI is being used to digitize and modernize manufacturing operations, contact us for a personalized demo.

Performance Management in Manufacturing: Best Practices and Examples

Learn about the best practices for optimal asset maintenance performance and how to track your assets to ensure that everything is in working condition.

Manufacturing performance management is the process of setting, monitoring, and optimizing key performance indicators (KPIs) related to production processes and workforce performance in manufacturing environments. It includes real-time monitoring and evaluation of employees’ work, as well as the continuous improvement of operational workflows to ensure optimal efficiency, product quality, and adherence to both safety requirements and organizational goals.

performance management in manufacturing best practices

Through data-driven insights, performance management software, and regular assessments, performance management aims to enhance employee productivity, reduce downtime, and maintain a competitive edge in the industry. Read our blog post below to learn more about performance management in manufacturing including:

5 Best Practices for Performance Management in Manufacturing

To get the best value from your performance management system here are five best practices for performance management in manufacturing:

1. Clear Goal Alignment:

Organizations must ensure that performance management processes align with overall organizational goals. They must clearly communicate objectives to employees at all levels, linking individual and team performance metrics to broader manufacturing and business objectives. This fosters a sense of purpose in frontline teams, engages workers, and helps employees understand how their efforts contribute to the company’s success.

2. Real-time Monitoring and Data Analytics:

Implement real-time monitoring of production and shop floor processes and equipment performance through the use of AI and connected worker technology. Utilize data analytics and AI-driven processing to gain insights into worker performance trends, identify bottlenecks, and facilitate data-driven decision-making. The ability to monitor operations in real-time not only enables proactive interventions to maintain efficiency, it also ensures fairness, accuracy, and transparency in performance measurement.

Pro Tip

Performance management software in manufacturing is crucial for optimizing production efficiency, and should integrate with other manufacturing systems, such as Learning Management Systems (LMS), Enterprise Resource Planning (ERP), and Manufacturing Execution Systems (MES), to provide a holistic view of the entire manufacturing operation.

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3. Employee Training and Development Programs:

Prioritize ongoing training and development programs for manufacturing personnel. Equip frontline workers with the necessary skills to adapt to evolving technologies and operational requirements. Use performance management systems and other digital tools like skills matrixes to identify skill gaps, set training goals, and track progress, ensuring a skilled and adaptable workforce.

4. Regular Performance Reviews and Feedback:

Conduct regular performance reviews that provide constructive and timely feedback to employees. Use these reviews as opportunities to recognize achievements, address areas for improvement, and set new performance goals. Foster open communication between managers and employees to encourage continuous improvement.

5. Integration with Continuous Improvement Initiatives:

Integrate performance management systems with “kaizen” or continuous improvement initiatives such as Lean or Six Sigma. Use data from performance metrics to identify opportunities for process optimization, waste reduction, and efficiency improvements. This ensures that performance management is not only evaluative but actively contributes to the ongoing enhancement of manufacturing processes.

Leveraging these best practices contributes to a holistic performance management process that aligns manufacturing organizations and their frontline workforce with strategic goals, optimizes operations, and creates a culture of continuous improvement.

Key Performance Management Strategies for Manufacturing Leaders

The following are a few examples of performance management strategies that manufacturing leaders, plant managers, and shift supervisors should consider when implementing their performance management process.

Line-shift Goals

Manufacturers often use production planning and scheduling systems to manage line shifts effectively and ensure a smooth transition between different production configurations. While line shifts in manufacturing are often necessary for adapting to changing demands, introducing new products, or optimizing efficiency, they can also pose challenges, including downtime, quality control issues, employee fatigue, and planning issues. By establishing clear and measurable objectives for each line shift or individual worker that aligns with organizational goals, production leaders can ensure production goals are met.

Individual Meetings and Communication

Manufacturing leaders should implement a performance management strategy that incorporates 1-1 meetings and communication. Regularly providing constructive feedback to employees on their performance can improve performance and boost employee engagement. Offering coaching and development opportunities to enhance skills and capabilities.

Continuous Training

Continuous training in manufacturing involves enabling workers to learn new skills regularly. It’s a great way to improve employee performance and innovation, as well as engage and retain top talent. A good example of a continuous learning model is everboarding, a modern approach toward employee onboarding and training that shifts away from the traditional “one-and-done” onboarding model and recognizes learning as an ongoing process.

Performance Management Tools

Implementing performance management tools can help automate ongoing employee evaluation, as well as align employee performance with other key manufacturing KPIs, including production quality, machine uptime, and labor utilization. These tools can also be used to identify continuous improvement opportunities. This allows manufacturing leaders to adapt and refine approaches based on feedback and outcomes.

Simplifying Performance Management with Digital Tools

According to Forbes, as the future of work evolves and changes so must performance management, traditional methods may no longer be as successful in an era where the workforce is constantly changing.

Digital tools such as connected worker solutions and AI-driven analytics help simplify performance management systems by streamlining processes, improving efficiency, and providing more accurate insights. Implementing these connected worker solutions automates the collection of performance-related data from various sources including connected frontline workers, IoT devices, software systems, and more. This eliminates the need for manual data entry, reducing errors and ensuring real-time access to up-to-date information.

By digitizing the performance management process, organizations create a centralized platform for storing and managing performance-related data. This centralized knowledge base makes it easy for managers and employees to access relevant information, track progress, and collaborate on performance goals. Furthermore, AI-driven connected worker solutions allow for digital performance tracking, customized training and skills development planning, workflow optimization, and improved predictive maintenance.

digital skills management in a paperless factory

Through these digital tools and technology, manufacturing companies can simplify performance management processes, improve operational efficiency, and adapt to the demands of a rapidly evolving industry while fostering a culture of continuous improvement and development for their manufacturing workforce.

Augmentir is the world’s leading connected worker solution, combining smart connected worker and AI technologies to drive continuous improvement and enhance performance management initiatives in manufacturing.

Augmentir is trusted by manufacturing leaders as a digital transformation partner improving training and development, workforce allocation, and operational excellence through our AI-driven True Productivity™ and True Performance™ offerings, as well as digitizing and optimizing complex workflows, skills tracking, and more through our patented smart, connected worker suite. Schedule a live demo today to learn more.

 

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Onboarding vs. Training in Manufacturing

Learn about the best practices for optimal asset maintenance performance and how to track your assets to ensure that everything is in working condition.

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:

Onboarding

  • 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.

Training

  • 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.

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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, onboarding and training in manufacturing are essential 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 training and onboarding process, 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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The Difference Between Skills Development and Training in Manufacturing

Learn about the best practices for optimal asset maintenance performance and how to track your assets to ensure that everything is in working condition.

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.

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.

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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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How to Apply Everboarding to the Factory Floor

Learn about the best practices for optimal asset maintenance performance and how to track your assets to ensure that everything is in working condition.

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.

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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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Using AI to Operationalize Training for Manufacturers

AI and connected worker technology is helping frontline managers combat employee burnout and improve engagement and retention.

In today’s fast-paced manufacturing industry, staying ahead of the curve is critical to success. To remain competitive, companies must continuously reskill and upskill their workforce.

One way to achieve this is by operationalizing learning and bringing it closer to the factory floor using artificial intelligence (AI) and connected worker technology. Operationalizing learning means taking a more systematic approach to training and workforce development, rather than treating it as a one-time event.

operationalizing learning

According to a report by McKinsey, companies that embrace AI-powered learning reduced training time by up to 50% and improved learning outcomes by up to 60%. AI-powered solutions make learning more accessible, engaging, and effective; and by integrating training and learning solutions into the everyday operations of the company, manufacturers can create a culture of continuous learning and improvement. In fact, here at Augmentir we’ve seen manufacturing companies use this approach to reduce new-hire onboarding and training time by up to 72%.

Learning: When and Where it’s Needed

AI has the potential to revolutionize many industries, and manufacturing is no exception. Many workers in the manufacturing industry work in shift-based environments, making it difficult for them to attend traditional classroom-based training sessions.

With AI, organizations can incorporate more learning processes into the everyday workday of frontline workers – essentially bridging the gap between knowing and doing. This “active learning” aligns with the Pyramid of Learning visual model that illustrates the different stages of learning and their relative effectiveness.

pyramid of learning

Active learning involves the learner actively engaging with the material, often through problem-solving, discussion, or application of the knowledge while they are on the job.

In general, active learning (or workflow learning) is considered more effective than passive learning in promoting deep understanding and retention of information. Therefore, learning leaders often strive to design learning experiences that involve higher levels of active learning, moving beyond the lower levels of the pyramid and promoting critical thinking, creativity, and problem-solving skills.

This approach 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 customized to each worker’s skill level, making it easier for them to learn at their own pace.

Additionally, AI-driven learning solutions offer:

  • Personalized Learning: AI-powered learning solutions can be customized to each worker’s skill level, making it easier for them to not only learn at their own pace, but also matched to their experience level. For example, novice workers may be required to watch a micro-learning video as a safety prerequisite to performing a task, whereas a more senior worker with the appropriate level of job experience and proficiency may not be required to watch the learning video.
  • Performance-based Learning: AI-powered solutions provide workers with hands-on learning experiences that are customized based on their actual job performance. These experiences can be delivered through a variety of content mediums – rich media, self-help guides, microlearning videos, and even augmented reality (AR) experiences.
  • Real-Time Feedback: AI-powered solutions can monitor worker performance in real-time, providing instant feedback to help workers improve to provide access to content to help resolve issues in the flow of work.

AI can also help with the assessment of employee performance. Traditional performance evaluations often rely on subjective assessments from managers. Conversely, AI-powered performance evaluations can provide a more objective and data-driven assessment of employee performance, while also providing a more accurate picture of an employee’s strengths and weaknesses.

Better Training, Better Work

By implementing AI-based solutions, companies can identify training needs across the organization. Using performance data, AI can uncover gaps in knowledge or skills across the workforce, which can then be used to develop targeted training programs to “fill” these gaps.

Once implemented, AI can be used to effectively track and improve learning and training effectiveness, leveraging data on worker performance before and after training to measure impact and refine training programs to ensure that they are delivering the best outcome.

As the manufacturing industry continues to evolve, so must how they approach learning solutions. A recent Deloitte survey found that over 90% of companies believe that AI-powered learning will be important for their organization’s success in the next three years. AI has the potential to transform learning in the manufacturing industry by bringing it closer to the factory floor. By leveraging AI-powered personalized learning, real-time feedback, data-driven performance evaluations, and identifying training needs, industrial organizations can create a more efficient, effective workforce.

Modernizing Manufacturing Training with Continuous and Workflow Learning

Learn about the best practices for optimal asset maintenance performance and how to track your assets to ensure that everything is in working condition.

Staying ahead of the curve in today’s manufacturing marketplace means that businesses need to innovate and adapt. To accomplish this, organizations must have a skilled workforce and ongoing training and workforce management processes to support continuous learning and development.

Modernizing training cultivates employee skillsets by implementing continuous learning in the flow of work.

modernize manufacturing training with continuous learning

Continuous learning is the process of attaining new skills on a constant basis. Workflow learning involves educating yourself on the job using resources and self-directed learning materials. Done together, this modern training approach can help streamline productivity.

If you want to learn how to improve manufacturing training with continuous learning and workflow learning, explore this article that answers the following:

What is continuous learning?

Continuous learning in manufacturing involves enabling workers to learn new skills regularly. It’s a great way to improve employee performance and innovation. According to Forbes, embracing a culture of continuous learning can help organizations adapt to market demands, foster innovation, as well as attract and retain top talent.

Learning can come in different forms, from formal course training to hands-on experience. Employees are encouraged to be self-starters who want to evolve their skills on an on-going basis. A good example of a continuous learning model is everboarding; everboarding is a modern approach toward employee onboarding and training that shifts away from the traditional “one-and-done” onboarding model and recognizes learning as an ongoing process.

How can continuous learning be used in manufacturing?

When businesses don’t support continuous learning, manufacturing processes stagnate. This contributes to a lack of innovation and hinders potential opportunities for success that a company may experience.

In a nutshell, the more workers know and the more they can accomplish, the more they can contribute to business growth. This may consist of employees taking an online course or learning a new technique hands-on, no matter what department they’re in.

For example, assembly line workers may learn new manufacturing processes to ensure everything is functioning properly. Meanwhile, operators may study the latest machinery to learn new tricks of the trade.

What is workflow learning?

Workflow training in manufacturing involves learning while doing. This means that workers pick up new skills while on the job through hands-on experience.

The key to workflow learning is that it happens while employees perform their everyday tasks.

Many workers in the manufacturing industry work in shift-based environments, making it difficult for them to attend traditional classroom-based training sessions. With workflow learning, organizations can incorporate more learning processes into the everyday workday of frontline workers – essentially bridging the gap between knowing and doing. This “active learning” aligns with the Pyramid of Learning visual model that illustrates the different stages of learning and their relative effectiveness.

pyramid of learning

Active learning involves the learner actively engaging with the material, often through problem-solving, discussion, or application of the knowledge while they are on the job.

In general, active learning is considered more effective than passive learning in promoting deep understanding and retention of information. Therefore, learning leaders often strive to design learning experiences that involve higher levels of active learning, moving beyond the lower levels of the pyramid and promoting critical thinking, creativity, and problem-solving skills.

How can workflow learning be used in manufacturing?

Workflow learning consists of using resources at your disposal to complete tasks. This strategy is sometimes referred to as performance support.

For example, workers can look up answers to questions, steps of a process, or new services while performing their jobs instead of interrupting their workflow to go to a class or training session.

Pro Tip

Active, or workflow learning 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.

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How can technology improve manufacturing training?

The nature of manufacturing training is changing in the age of artificial intelligence. Today, many training processes can be streamlined and optimized using digital and smart, connected worker technologies.

For instance, data collected from everyday manufacturing processes can polish training programs online. Experienced workers can share best practices on customized dashboards for other employees to access. These can be updated in real-time and show changes highlighted to better optimize manufacturing processes.

Digital training tools can also help improve learning speed and retention. For example, workers who need visuals or real-world scenarios can assess them using AI-powered software to maximize their training.

 

Augmentir is the world’s leading AI-powered connected worker solution that helps industrial companies optimize the safety, quality, and productivity of the industrial frontline workforce. Contact us for a live demo, and learn why leading manufacturers are choosing us to elevate their manufacturing operations to the next level.

 

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