How to Apply Everboarding to the Factory Floor

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.

A

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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Darwin in Manufacturing: The Evolution of Connected Worker Software

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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The Connected Enterprise: Why a Connected Worker Strategy is Critical to Success

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

If you are interested in learning for yourself why companies are choosing Augmentir to help them connect, digitize, and optimize their frontline operations – reach out to book a demo.

 

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Why You Should Digitize and Standardize QA and Inspection Procedures

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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Autonomous vs. Preventive Maintenance

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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How Skills Tracking Improves Work Allocation and Workforce Utilization

Learn how skills tracking enhances work allocation and workforce utilization to improve productivity in manufacturing.

Employee skills tracking is an excellent way to stay ahead of the curve in today’s ever-changing manufacturing landscape. Leaders can use this talent management strategy to close worker competency gaps, increase effective training, and hire qualified prospects.

Putting an emphasis on employee skills can also help manufacturers prioritize work allocation and workforce utilization. But what exactly do these two terms mean and how do they relate to tracking skills in manufacturing?

Work allocation is the process of assigning resources and roles to meet the objectives of a given task or production facility. Workforce utilization, meanwhile, refers to how a company or organization effectively utilizes its workforce to meet its operational goals and objectives.

skills tracking and workforce utilization in manufacturing

To keep up with competition, manufacturers should not only try to recruit the best possible hires, but also allocate work in an effective way to retain staff, satisfy customers, and boost profits.

Ultimately, keeping track of skills is a beneficial way to organize a company’s resources to attain sustainable business goals. Implementing a connected worker solution and digitizing skills management processes through smart manufacturing technologies is an effective way for organizations to instantly visualize the skills gaps in teams as well as track workforce skills and quickly assess both team and individual readiness.

Learn more about digital skills tracking and how it improves work allocation and workforce utilization below:

Skills tracking defined

Skills tracking helps ensure that all workers have the necessary expertise to complete tasks to their fullest potential. Basically, it closes the gap between the competencies employees already have and ones they need to further develop.

Every manufacturing firm has a unique set of job requirements and expectations. Tracking worker skills on a regular basis helps a company identify training needs and build workers’ knowledge so that they can meet expected targets. Skills management and tracking software help manufacturers identify and track employee expertise. You can map skills from a centralized library to individual workers, analyze the performance of your teams, and fill any skill gaps that exist.

skills tracking software

In a nutshell, measuring employee proficiencies can boost retention, decrease the amount of time spent on tasks, and improve overall productivity.

Benefits of tracking skills to improve work allocation

Through digitization and effective skills tracking, manufacturing firms can best allocate work to team members based on expertise, credentials, and actual ability. For example, an operator who has more than 10 years of experience using computer-controlled equipment may be a better fit to handle complex machinery than an entry-level worker who lacks that training.

Additionally, with a centralized digital repository managers have a better idea of each employee’s current skills level and potential areas of improvement. Then they can close any skill gaps through training opportunities. In return, workers who receive the necessary training are more likely to thrive in their roles and be productive.

In summary, measuring worker skills can help improve work allocation by:

  • Hiring or assigning current employees to the correct jobs and tasks
  • Facilitating worker development through mentorship and training
  • Retaining high-quality employees

How tracking skills boosts workforce utilization

Workforce utilization refers to how much of an employee’s time is devoted to billable work. Tracking skills can improve this, in turn boosting productivity and profits.

When you measure how efficiently employees are doing their jobs and how well a business manages its resources, you can assure that tasks are done well and see continuous increase in revenue. Think about how many hours of each staff member’s workweek need to be billable to remain profitable and whether they are on track. With a digitized tracking system, manufacturers are able to automate and streamline this process reducing errors, improving productivity, and ensuring success.

Pro Tip

Through the use of smart, connected worker solutions and AI-based workforce insights organizations can deliver continuous, on-the-job learning based on skill tracking and real job performance, promoting reskilling and upskilling efforts enterprise wide.

To summarize, tracking skills can help enhance workforce utilization by:

  • Setting profitable rates for services based on worker output and time billed
  • Compensating employees fairly
  • Gauging whether staff is being overworked or underutilized

By digitizing these tracking processes and implementing AI-driven support, organizations can also visualize, track and offset employee burnout. By taking highly granular connected worker data and using AI to filter out the unnecessary portions, industrial operations are able to not only improve tasks and productivity but better support and empower frontline workers.

Ways to track workforce skills

Tracking employee skills is a great way to improve worker performance and productivity by matching the right person with the right assignment.

One way to track an employee’s skills is through a skills matrix, which is a grid that maps staff credentials and qualifications. A skills matrix helps managers strategize and oversee current and wanted skills for a team, position, department, and more. A skills matrix is usually managed using a spreadsheet, but there are alternatives to skill matrices. For example, cloud-based skills management software can help identify and track employee competence and correlate it with actual job performance. The software can also help managers filter employee databases by skills to assemble teams or assign work based on specific qualifications.

skills matrix

Leadership can also track competencies through a skills taxonomy. Taxonomies help classify and organize skills into groups to better understand which skills employees have and which they should learn. Essentially, these structured lists help management identify and track skills to better allocate resources and worker training opportunities.

Lastly, a skills-tracking application can include AI-based software to identify and measure worker expertise and actual job performance. This is an excellent method for intelligently assigning work through skills mapping, optimizing training programs, and more. With AI-based insights and connected worker technology, organizations can bridge the gap between the training room and the shop floor, integrating training into the flow of work and creating an environment of continuous learning.

Skills management with Augmentir

Augmentir offers top-notch solutions to easily track and manage your frontline’s skillset. Our connected worker solution provides customized dashboards to streamline processes to improve workforce management, skills management, and deliver in-line training and support at the point of work, closing skills gaps at the moment of need.

If you are interested in learning how Augmentir can help improve your skills management, skills tracking, and workforce development – request a live demo.

 

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Why Quality is Important in Manufacturing

Learn why implementing quality in manufacturing is crucial for product creation, risk management, and more.

Quality in manufacturing depends on effective quality control (QC), a set of procedures used to measure and test products for compliance. The main function of QC is to ensure that all goods are free of defects, meet client expectations, and adhere to industry best practices.

Products have the potential either to increase customer satisfaction or to create legal and financial complications if deficiencies are found. In the current era where consumers are increasingly conscious of product safety and quality, it is paramount that manufacturers are doing all they can to ensure products meet all quality standards. Quality goods can affect a business’s success and advance its credibility to the public. They can also lead to fewer production costs and increases in profit.

With emerging digital technologies such as AI and connected worker solutions, manufacturers can improve quality control, decrease defects, and more. AI-powered connected worker platforms allow manufacturers to standardize quality control, resulting in fewer errors, reduced defects, and streamlined quality processes that are faster and more accurate.

Explore the following content to get a better idea of why quality is crucial and ways to improve it:

quality in manufacturing

Defining quality on industrial frontlines

Quality in the manufacturing realm is all about following procedures to meet product and compliance specifications. Once the standard for quality is set, the rest is about meeting product expectations through standardized procedures.

Quality in production can be broken down into three factors: design, quality control, and quality management.

Design: A product can be significantly improved by design. For example, goods should be made with the right materials to ensure functionality and a longer shelf life.

Quality control: The level of quality is improved when waste and product defects are reduced during the QC process.

Quality management: Completing production processes that follow regulatory standards is at the core of quality management.

Pro Tip

By digitizing quality control and quality assurance procedures, manufacturers can ensure a standardized approach towards inspections and quality data collection and improve overall compliance with quality standards.

Quality affects every facet of manufacturing

Production quality is more than just distributing products that people will trust and buy. Though that may be a key factor, quality affects every aspect of manufacturing, from workplace risk management to machine upkeep and inspection.

Quality affects many aspects of production. Examples include the following:

  • Risk management ensures products are safe to use by customers and follow safety protocols. Smart, connected worker solutions are able to improve risk management through standardization and optimization of quality checks.
  • Regulatory compliance is a key component of quality and can help prevent delays in production and fines. With digitized processes in place, manufacturers are able to ensure workers have access to the correct procedures and that tasks are performed in a standardized manner to avoid errors and promote improved compliance.
  • Waste reduction is possible when material resources are conserved and used accordingly in production processes. AI-powered analytics in conjunction with smart, connected worker solutions allow for improved, streamlined processes that are able to reduce waste and improve yield through optimized production.
  • Errors and defects are reduced when procedures are standardized using efficient QC processes to troubleshoot problems. With connected worker solutions and digitized quality control processes, mistakes can be identified as they happen, protecting the production process.
  • Machine upkeep and inspection can be strengthened when industry best practices are implemented. Digitizing machine inspection standards and upkeep notifications and connecting frontline workers via smart, connected worker platforms gives operators the ability to practice preventative and autonomous maintenance and improves overall equipment effectiveness (OEE) and reduces unplanned downtime.

How to Improve Quality in Manufacturing

Quality improvement in manufacturing is vital to ensure a business is performing at its best. Here are some ways to boost quality with real-world examples:

Step 1: Practice lean manufacturing.

Lean manufacturing is the practice of reducing waste in production processes. Waste is defined as anything that does not bring value to the customer. This method requires an examination of your current practices to see which work and which leads to greater waste. The rise of digital technology is making it easier and more practical for manufacturers to connect and digitize their operations and drive further improvements and enhance lean manufacturing strategies.

Real-world application: An injection molding machine was found clogged with mold and was producing products with damaged seams. After resolving this issue by cleaning the machine, the company had less wasted plastic and fewer product malfunctions. With digitized notifications, real-time collaboration, and smart, connected worker solutions, situations like the above can be solved quickly and with reduced impact on production.

standardize and digitize quality assurance procedures

Step 2: Implement total productive maintenance.

Total Productive Maintenance (TPM) focuses on the idea that every employee should do their part to maximize equipment effectiveness. The objective is to create a culture where every worker adjusts and maintains machinery over the course of each shift. Through a combination of digital work instructions and real-time collaboration tools, manufacturers can better implement and improve TPM initiatives. This allows operators to independently complete maintenance tasks at peak performance and improve overall equipment effectiveness (OEE).

Real-world application: Both operators and maintenance staff can perform routine maintenance to check for errors or deficiencies. By implementing connected worker solutions organizations can improve the quality, transparency, and efficiency of maintenance and repair procedures and minimize machine downtime and reduce overall maintenance costs and impact.

Step 3: Embrace statistical process control.

This method involves detecting production issues by studying data anomalies to get rid of root causes before they ruin entire assembly lines. With connected frontline worker solutions that are integrated with enterprise quality management systems, organizations can improve statistical process control by optimizing data collection and inspection procedures through their frontline workforce. This essentially transforms frontline workers into quality sensors that further enhance and empower overall quality efforts.

Real-world application: Tracking the number of defective goods on each production line can help with identifying the root of any issue and taking corrective action. Smart, connected worker technology improves tracking ability, optimizes data collection, and identifies issues faster, reducing the risk of product recalls, and preserving consumer trust.

Digitizing Quality in Manufacturing with Augmentir

Companies are adopting innovative new technologies, processes, and methods to improve quality, productivity, and collaboration efforts across the industrial arena. Guaranteeing quality in manufacturing boils down to standardizing processes. Every procedure should contribute to product value and be carried out in a unified way. Implementing smart, connected solutions and coupling them with AI-powered analytics opens new paths for manufacturers to step forward and improve how they approach quality in the production process and beyond.

By digitizing analog paper practices, you enable better quality control and standardization of inspection procedures which, in turn, strengthens your overall manufacturing operations. Augmentir can help with the digitization and transformation process. We understand the need for effective quality control, and we have demonstrated success in helping manufacturers improve quality on the production floor.

Check out our quality use cases, and request a live demo today to learn for yourself why companies are choosing Augmentir to help standardize and digitize quality control procedures.

 

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How an Asset Hierarchy Can Help with Asset Maintenance

Learn about what an asset hierarchy is and how it can help with asset maintenance and equipment reliability.

An asset hierarchy outlines all of a business’s top equipment, machines, and components visually to help the business plan, execute and track maintenance activities. Asset hierarchies are usually in the shape of a pyramid, similar to an organizational chart. And since every operation is different, it’s likely you won’t have the same hierarchy as your competitor.

The benefits of an asset hierarchy include accurate maintenance planning, faster failure root cause analysis, and improved cost tracking. By implementing an asset hierarchy in conjunction with a frontline operations system, such as a connected worker solution, manufacturers can benefit by dramatically improved maintenance planning and execution. This article answers the following questions to help you learn more:

asset hierarchy improves maintenance

What is an asset hierarchy?

An asset hierarchy is an index of your most critical equipment, machines, and parts to better understand how these assets work together and monitor their maintenance needs. For example, building and maintaining your manufacturing business’s hierarchy can help you track and identify root causes of failure in your equipment.asset hierarchy and taxonomy - iso standard

This taxonomy is often represented as a pyramid, based on the ISO 14224 standard, which was developed for the collection and exchange of
reliability and maintenance data for equipment. Initially developed for the Petroleum, Petrochemical, and Natural Gas industry, this taxonomy for equipment and failure data can apply to any manufacturing environment, and has become the de-facto standard for every other industry.

Asset hierarchies are typically built and maintained within an organization’s EAM (Enterprise Asset Management) or CMMS (Computerized Maintenance Management System), which tracks asset maintenance and condition data, as well as maintenance schedules. Increasingly, EAMs, CMMS, and asset hierarchy information are being integrated with digitized frontline operations systems to improve maintenance planning and execution.

Pro Tip

It’s not enough to simply define your asset hierarchy with your EAM or CMMS. Innovative manufacturing companies are now extending this by integrating their asset hierarchies with connected worker solutions, which help digitize and optimize the actual work being done by frontline maintenance teams, improving maintenance execution.

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Better organization of equipment can also help workers understand how the action of one affects the other to solve any potential problems. This is another benefit of integrating your asset hierarchy with a connected worker solution. In a nutshell, strong hierarchies are a solid foundation for proper maintenance management and reliability.

What is asset maintenance?

While maintenance is generally synonymous with repair, in effective manufacturing facilities, maintaining equipment can prevent the need for repairs. Asset maintenance is an umbrella term for everything that goes into keeping your assets in tip-top shape.

For example, asset maintenance in manufacturing machinery may mean frequent inspections to prevent breakdowns and repairs. Your space as a whole relies on this type of maintenance to ensure everything is running smoothly, from equipment to everyday production processes.

Lastly, this term makes daily manufacturing processes more productive to manage. That’s because effective asset management tells you where assets are located, how they are used, and when changes were made to them.

How does an asset hierarchy improve asset maintenance?

An asset hierarchy and asset maintenance work in conjunction with one another. This visual tool gives workers a better idea of what each asset is and the dependencies between them.

Knowing what each asset is can help you schedule preventative inspections and tasks. If any problems arise, you can more easily identify all the working parts, find the root cause and fix it.

 

Augmentir’s AI-powered asset management software helps you simplify the operations and maintenance of your facility by integrating your asset hierarchy and maintenance data within a frontline operations system. Through Augmentir, organizations can benefit from a complete view of asset management, all through a visual mobile interface. Each asset contains a complete view of:

  • Kanban board for all asset activities
  • Work and maintenance procedures
  • Skills required for operation and maintenance
  • Collaboration related to the asset
  • Associated documentation
  • CIL/Standard Work schedule
  • History of all activities on the asset

Asset management with Augmentir

Augmentir’s asset management capabilities include an out-of-the-box autonomous maintenance solution, which gives equipment operators more control over equipment cleaning, inspections, and lubrications (CIL) to improve CIL completion rate, resulting in minimized machine downtime.

Request a live demo today to learn why companies are choosing Augmentir to help standardize and digitize their maintenance activities.

 

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