LNS Research reviewed dozens of Connected Frontline Worker (CFW) vendors, ranking Augmentir as the leading CFW solution innovator.
Efforts to enable the frontline industrial workforce through connected worker and other digital technologies have become increasingly common over the past several years, recently, LNS Research found that over half of industrial organizations globally have undertaken Connected Frontline Workforce (CFW) initiatives. CFW has become a strategic part of Industrial Transformation (IX) initiatives as manufacturers seek to solve critical labor shortages, skills gaps, and retention issues in frontline operations.
CFW-enabling technologies hold the promise of helping companies meet their frontline workforce challenges while optimizing operational performance across safety, quality, and productivity dimensions. However, industrial business and technology leaders must navigate the uncertain waters of the relatively immature and highly fragmented CFW Applications market to capture the opportunity fully.
From their extensive analysis, LNS Research has created the CFW Applications Solution Selection Matrix™ (SSM) – a comprehensive guide intended to help manufacturers better understand, evaluate, and even select from a shortlist of Connected Frontline Worker technology vendors.
LNS Research reviewed dozens of vendors within the CFW ecosystem and categorized them based on various key criteria, including product capabilities, market potential, and company presence. Augmentir was named by LNS Research as a leading CFW solution innovator in their SSM.
Augmentir positioned as a leading front runner and innovator
According to LNS Research, Augmentir is well-positioned for future growth, with a trajectory that gives it the potential to be among a small set of likely market leaders in the Connected Frontline Worker (CFW) Applications space. This assessment is based partly on the strength of differentiated capabilities of its AI-enabled solution suite to enable proactive, data-driven performance improvement, personalization of work execution support and training, and the integration of individual and team skills and qualifications to guide workforce development and shift-specific work assignment.
Other key factors impacting Augmentir’s potential are the strength and proven experience of the leadership and management teams, strong momentum in the market, a record of successful product innovation, ecosystem partnerships, and likely continued access to adequate funding and resources to support the expansion of go-to-market initiatives. Augmentir’s track record indicates a strong likelihood of continued growth and the potential over time to be among a select group of market leaders in the CFW Applications space.
Manufacturers are using connected frontline worker solutions to empower their employees with real-time, actionable data; driving better decision-making and improving safety, training, and more.
Leading manufacturers that deployed Augmentir’s AI-driven, smart, connected worker solution have seen impressive results, such as:
75% reduction in new hire training/onboarding time
27% reduction in machine downtime using Autonomous Maintenance
32% improvement in worker productivity
In addition to the above results, our customers have seen quality, safety, and productivity increases across all operations, as well as increases in employee retention and reductions in operating costs associated with employee churn.
If you are interested in learning why LNS Research ranked Augmentir as the leading connected worker solution in the market, reach out to us and request a live demo.
Learn how to improve quality control and assurance in the food industry with digital solutions from Augmentir.
Following quality control (QC) and quality assurance procedures in the food industry is imperative to ensure product quality and consumer satisfaction. Today’s consumers demand safe, reliable goods that meet all quality inspection protocols. The last thing you want is for a product to get recalled because of potential health concerns.
According to Food Manufacturing, quality control is one of the most important aspects of the food and beverage industry. Manufacturers who perform routine inspections of products during each stage of the production process significantly increase their chances of delivering items that are free of health hazards and liabilities. But beyond avoiding these concerns, standardizing and digitizing quality procedures benefits the entire operation.
Ultimately, preventing and catching quality issues can boost product quality, reduce waste, raise profits, increase brand reputation, and avoid media or food safety disasters. Learn more about QC and assurance in the food industry and how to improve it as we discuss:
There are certain QC measures you can take to ensure that all goods meet quality standards, from regular machine inspections to worker training. They fall into two general categories: preventative and reactive.
Preventative (proactive) quality control: Minimizing the number of deficiencies begins with implementing preventative QC solutions. When workers can catch mistakes before they even happen, they prevent product defects. Preventative QC measures should be practiced on a routine basis and can range from inspecting machines and equipment to offering employee training opportunities. By providing workers with real-time information and guidance through mobile, connected worker solutions, manufacturers enable them to make better decisions about product quality, reducing the risk of errors and identifying potential quality issues before products are shipped to customers, reducing the risk of product recalls, and preserving consumer trust.
Reactive quality control: Catching every defect on the production floor is nearly impossible, even if the most fool-proof strategies are taken. That’s why creating a plan of action ahead of a crisis can help solve quality issues as they happen.
What to put in your plan will depend on the potential problems. For example, you can include specific instructions on what to do if machinery breaks down or stops unexpectedly. It’s vital to collect any data at this stage. Analyzing this data can help you improve preventative quality control in the future to make sure the same problems don’t happen again.
Pro Tip
By utilizing AI and modern, digital technologies, companies can connect, engage, and empower frontline workers to drive quality improvements, resolve quality issues faster, and share timely insights with teams across the value chain.
Keep in mind that practicing quality control in the food industry should be part of every manufacturing process, from product ideation and development to production and delivery. Problems can develop at any time, so it’s crucial to follow protocols at every stage of production to prevent even the slightest of mistakes.
All workers should also uphold QC and assurance protocols in their everyday tasks to ensure continuous product improvement.
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.
How to improve QC and assurance procedures in food production
Effective quality control and assurance procedures prevent defective food products from making their way into grocery stores and homes. That’s why manufacturers should document the quality of their goods at every stage of the operational process. Strategies like first time quality (FTQ), or first time right, plans coupled with smart, connected solutions help decrease product deficiencies and increase customer satisfaction.
Manufacturing firms in the food industry must follow specific requirements set by the Food and Drug Administration (FDA), Good Manufacturing Practices (GMP) system, and the Hazard Analysis and Critical Control Points (HACCP). The guidelines set by these regulatory bodies can give businesses a better idea of how their processes should look and what data they need to collect and report.
Data should be collected for real-time production processes. These vary by product but may range from product chilling and thermal processing to testing raw materials for metal toxins and other chemical deposits.
The following steps provide a roadmap for how to improve quality control in the food industry.
Step 1: Source the correct ingredients
A successful assembly line run begins with finding and using the correct ingredients. Some things to think about when deciding which ingredients to choose: where the raw material was sourced, when, and its condition.
Step 2: Include an approved supplier list
Make sure that each ingredient has an approved supplier list. A good rule of thumb is to include three vendors per ingredient and record the ingredient with each supplier’s name, address, and code number on the list. The more information you include, the better. Having an approved vendor list ensures that all parties are properly vetted by the manufacturing firm and meet its requirements for quality and distribution.
Step 3: Document product and recipe creation
Documenting how each food item is made and its recipe helps set the quality standards for finished goods. This documentation can also be useful when improving product development in the future. Your document should include the types of ingredients used, their codes, batch yield, percentage formula, and more.
Step 4: Catalog production procedures
It’s also critical to log all the details of a production process, including how materials should be delivered, the appropriate conditions for storing food, what order each ingredient should be added to the batch, what tools are needed, and who is in charge of each task.
Note that this step is different from documenting product and recipe development because it includes the actual instructions for carrying out each procedure. For example, a worker may be asked to preheat the oven to a certain temperature as part of ensuring the food is ready for customer distribution.
Step 4: Record real-time processes
Machine operators should record in real-time every detail of how goods are created during actual production. This can include factors like product size, weight, expiration date, equipment conditions, and more.
Step 5: Digitize assurance and inspection processes
AI and smart, connected worker systems help digitize and link inspections and other quality control procedures. This creates an additional layer of defense, protecting customers and preventing quality issues before they can impact production.
How Augmentir helps with quality control and assurance
Augmentir offers a smarter way to improve quality control in the food industry by effectively standardizing and optimizing quality assurance and inspection procedures for all frontline workers. With our smart, connected solutions coupled with AI-powered software, food manufacturers have improved quality control and assurance by:
Tracking and analyzing data to identify trends and opportunities for improvements
Reducing human error in inspections by standardizing and improving training procedures and processes
Transforming connected workers into human sensors who can proactively address quality and safety events that surface during manufacturing operations
Our AI-powered connected worker solutions, provide digital work instructions to help employees better perform inspection checks and reduce the number of production errors and rework.
These customized solutions also include:
Digital standard operating procedures (SOPs) for how to complete assembly line tasks. These step-by-step instructions can greatly improve workflow efficiency, increase regulatory compliance, and reduce mistakes on the shop floor.
Digital workflows that convert your paper-based processes to digital work instructions and personalize them to the needs of each worker.
Enhanced product traceability to decrease equipment setup time, reduce process inconsistencies, and better meet customer expectations. Our digital instructions help you to easily track materials from the supply chain, inventory, and across every production process.
If you are interested in learning why companies are choosing Augmentir to help improve their quality control and assurance processes, check out our quality use cases – or reach out to schedule a live demo.
https://www.augmentir.com/wp-content/uploads/2023/08/quality-control-food-industry.jpg6301200Chris Kuntzhttps://www.augmentir.com/wp-content/uploads/2021/09/Augmentir_Logo_Sm-300x169.pngChris Kuntz2023-08-15 02:53:172024-06-04 11:44:37How to Improve Quality Control and Quality Assurance in the Food Industry
Learn how to digitize your operations and build a paperless factory in this paperless manufacturing guide from Augmentir.
Manually managing and tracking production in manufacturing has become a thing of the past. That’s because manufacturers are adopting a new digital approach: paperless manufacturing.
Paperless manufacturing uses software to manage shop floor execution, digitize work instructions, execute workflows, automate record-keeping and scheduling, and communicate with shop floor employees. More recently, this approach also digitizes skills tracking and performance assessments for shop floor workers to help optimize workforce onboarding, training, and ongoing management. This technology is made up of cloud-based software, mobile and wearable technology, artificial intelligence, machine learning algorithms, and advanced analytics.
Paperless manufacturing software uses interactive screens, dashboards, data collection, sensors, and reporting filters to show real-time insights into your factory operations. If you want to learn more about paperless manufacturing processes, explore this guide to learn about the following:
A paperless factory uses AI-powered software to manage production, keep track of records, and optimize jobs being executed on the shop floor. Paperless manufacturing is intended to replace written record-keeping as well as paper-based work instructions, checklists, and SOPs, and keep track of records digitally.
For example, in most manufacturing operations, everything from quality inspections to operator rounds and planned and autonomous maintenance is done on a regular basis to make sure factory equipment is operating properly and quality and safety standards are met. In most manufacturing plants, these activities are done manually with paper-based instructions, checklists, or forms.
Operators and shop floor workers in paperless factories use software to execute work procedures and see production tasks in ordered sequences, which enables them to implement tasks accordingly. Workers are able to view operating procedures, or digital work instructions, using mobile devices (wearables, tablets, etc.) in real-time.
Furthermore, paperless manufacturing incorporates the digitization of shop floor training, skills tracking, certifications, and assessments. This digital approach uses skills management software helps optimize HR-based processes that were previously managed via paper or spreadsheets, and includes the ability to:
Create, track, and manage employee skills
Instantly visualize the skills gaps in your team
Schedule or assign jobs based on worker skill level and proficiency
Close skill gaps with continuous learning
Make data-driven drive operational decisions
What are the benefits of going paperless in manufacturing?
There are a number of reasons for factories to go paperless, from cost-effectiveness to increased productivity and sustainability. A paperless system can revolutionize production processes, workforce management, and business operations.
Here are the top benefits of going paperless:
Accelerate employee onboarding: By digitizing onboarding and moving training into the flow of work, manufacturers can reduce new hire onboarding time by 82%.
Increase productivity: Digitizing manufacturing operations means no more manual, paper-based data collection or record-keeping. Workers have more time to run their equipment, execute shop floor tasks, and find solutions to problems.
Boost data accuracy: People are prone to making mistakes, but digital data capture and validation can help offset human error and improve accuracy.
Improved workforce management: Digital skills tracking and AI-based workforce analytics can help optimize production operations and maximize worker output.
Manage real-time operations: Human-machine interface systems eliminate the need for paper, files, and job tickets. This means that workers can analyze inventory and other data in real-time.
Save money: Although going paperless means that the cost of paper is eliminated, the savings extend beyond that. With greater productivity, operations in real-time, and improved production optimization, costs can be reduced in many areas.
How do you go paperless in manufacturing?
Going paperless starts with digitizing activities across the factory floor to increase productivity, and extending that value through a digital connection between the shop floor and enterprise manufacturing systems. We lay out below the four basic steps for how to go paperless in manufacturing:
Step 1: Digitize and connect your frontline operations.
Paperless manufacturing starts with the use of modern, digital tools that can connect, digitize, and optimize what your employees know and how they are doing on the job. Solutions that incorporate enhanced mobile capabilities and combine training and skills tracking with connected worker technology and on-the-job digital guidance can deliver significant additional value. A key requirement to start is to identify high-value use cases that can benefit from digitization, such as quality control or inspection procedures, lockout tagout procedures, safety reporting, or autonomous maintenance procedures.
Step 2: Augment your workers with AI and Connected Worker technology.
AI-based connected worker solutions can help both digitize work instructions and deliver that guidance in a way that is personalized to the individual worker and their performance. AI Bots that leverage generative AI and GPT-like AI models can assist workers with language translation, feedback, on-demand answers, access to knowledge through natural language, and provide a comprehensive digital performance support tool.
As workers become more connected, companies have access to a rich source of job activity, execution, and tribal data, and with proper AI tools can gain insights into areas where the largest improvement opportunities exist.
Pro Tip
Frontline operations software like Augmentir’s Connected Worker Solution helps you digitize and optimize the operations of your facility. Digitally manage safety, quality, operations, and maintenance procedures, skill requirements, training, and KPIs all through a visual interface. Connected worker solutions help digitally integrate your shop floor operations.
Step 3: Set up IoT sensors for machine health monitoring.
The industrial Internet of Things (IoT) uses sensors to boost manufacturing processes. IoT sensors are connected through the web using wireless or 4G/5G networks to transmit data right from the shop floor. The use of machine health monitoring tools along with connected worker technology can provide a comprehensive shop floor solution.
Step 4: Connect your frontline to your enterprise.
Digitally connected frontline operations solutions not only enable industrial companies to digitize work instructions, checklists, and SOPs, but also allow them to create digital workflows and integrations that fully incorporate the frontline workers into the digital thread of their business.
The digital thread represents a connected data flow across a manufacturing enterprise – including people, systems, and machines. By incorporating the activities and data from these previously disconnected workers, business processes are accelerated, and this new source of data provides newfound opportunities for innovation and improvement.
Augmentir provides a unique Connected Worker solution that uses AI to help manufacturing companies intelligently onboard, train, guide, and support frontline workers so each worker can contribute at their individual best, helping achieve production goals in today’s era of workforce disruption.
Our solution is a SaaS-based suite of software tools that helps customers digitize and optimize all frontline processes including Autonomous and Preventive Maintenance, Quality, Safety, and Assembly.
Transform how your company runs its frontline operations. Request a live demo today!
https://www.augmentir.com/wp-content/uploads/2023/09/paperless-manufacturing-augmentir.webp6301200Chris Kuntzhttps://www.augmentir.com/wp-content/uploads/2021/09/Augmentir_Logo_Sm-300x169.pngChris Kuntz2023-09-20 14:12:392024-06-04 11:42:55Paperless Manufacturing: Your Guide to Transitioning to a Paperless Factory
Learn how to write manufacturing SOPs and the benefits of having standard operating procedures in a manufacturing operation.
Standard operating procedures, or SOPs, will change the way you run your manufacturing operations.
SOPs are imperative to a properly organized management structure. They are step-by-step guidelines workers must follow when carrying out tasks to standardize work and are designed to meet industry regulations.
Essentially, they provide general info about assignments, including the tools, methods, or machinery needed to complete projects. SOPs indicate what the task is, who will perform it, how it should be completed, and when it should be completed.
For example, manufacturers may write SOPs for employee training to reduce risk and injury. Leadership may also use procedures to assign goals and measure employee performance.
Read on to find out more about the benefits of manufacturing SOPs and how to write them by exploring the following topics:
Advantages of Implementing Standard Operating Procedures
According to Forbes, a comprehensive SOP keeps workers on the same page and improves efficiency and accuracy. Without documented procedures, there is no way to set proper standardized processes and workers might try to complete jobs in non-standard methods, which leads to disruptions in the production processes and causes all sorts of quality issues in a manufacturing environment. Thankfully, SOPs work to prevent that from happening.
Some of the advantages of using SOPs include:
Meets regulatory compliance: Product inspectors constantly ask to review SOPs when conducting audits. These serve as the point of reference for whether specific measures followed meet industry guidelines.
Standardizes tasks: The point of written procedures is to establish a standard way of completing tasks. They enable tasks to be performed in the same way across the company.
Improves accountability and tracking: SOPs define who is responsible for a work order, maintenance check or inspection. This reporting can improve accountability across departments. If a task wasn’t completed accordingly or a procedure was missed, management can take necessary steps to prevent it from happening again.
Pro Tip
Digitized SOPs can further improve tracking and traceability features, helping manufacturers comply with regulations and quality standards. With digital SOPs it becomes easier to maintain records of every step in the production process, including who performed each task and when.
How to write a manufacturing SOP
Writing a comprehensive set of SOPs can help workers perform tasks in the safest and most efficient way possible. Although there isn’t an official way to write procedures, you can follow certain steps to make them more effective:
Step 1: Establish a goal.
It’s important to think about what you want your SOP to accomplish. Regardless if you’re starting a new process or improving an existing one, figuring out the end goal will make it easier to complete the document.
Step 2: Pick a format.
There are different formats you can use to write your document: step-by-step, hierarchical, narrative, etc. We recommend the sequential step-by-step format for its straightforwardness.
Step 3: Write the procedures.
Make sure your procedures are clear, concise, current, consistent, and complete.
Step 4: Review and update.
It’s important to review your SOP for any discrepancies and update them if necessary. Consider asking fellow leaders knowledgeable in procedure creation to read them over.
Why SOPs are Important in Manufacturing
Compliance with manufacturing SOPs is crucial for a number of reasons, including:
Prevents accidents and ensures worker safety
Promotes worker consistency
Improves product quality
Protects your business’s reputation
SOPs are a critical component of manufacturing operations because they provide a structured framework for achieving consistent quality, safety, and efficiency in the production process. They help manufacturers meet regulatory requirements, reduce errors, and ensure that employees are trained to perform tasks consistently and safely.
Digitizing Manufacturing SOPs with Connected Worker Solutions
Using connected worker technologies to create digital SOPs can significantly improve their impact on manufacturing by enhancing accessibility, effectiveness, and overall utility.
Through digitization and smart, connected worker technology manufacturers can improve SOPs with features like real-time access, remote collaboration and guidance, data-driven insights, workflow automation, enhanced training, traceability and compliance, and more. Essentially, with these advanced technologies, manufacturing organizations can augment and support their workers with optimized processes and SOPs creating an environment of continuous improvement.
Augmentir offers customized AI-powered connected worker solutions that transform how you write and create manufacturing standard operating procedures. Request a live demo today to learn more about why leading manufacturers are choosing our solutions to improve their manufacturing processes.
https://www.augmentir.com/wp-content/uploads/2023/10/manufacturing-sop.webp6301200Chris Kuntzhttps://www.augmentir.com/wp-content/uploads/2021/09/Augmentir_Logo_Sm-300x169.pngChris Kuntz2023-10-14 02:10:262024-06-04 11:42:31Benefits of Manufacturing SOPs and How to Write Them
Learn how continuous and workflow learning can help modernize employee training in the manufacturing industry.
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.
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:
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.
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.
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.
https://www.augmentir.com/wp-content/uploads/2023/10/modernize-manufacturing-training.webp6301200Chris Kuntzhttps://www.augmentir.com/wp-content/uploads/2021/09/Augmentir_Logo_Sm-300x169.pngChris Kuntz2023-10-21 01:51:242024-06-04 11:42:12Modernizing Manufacturing Training with Continuous and Workflow Learning
Learn why integrations are key to the success of connected worker platforms, what systems should be integrated, and the benefits of a fully integrated connected worker solution.
Unlocking the potential of connected worker platforms becomes a game-changer when integrated with enterprise systems, giving them a live, closed loop connection to frontline processes and operations. This creates a truly connected enterprise that links diverse systems with the frontline workforce, paving the way for heightened efficiency, productivity, and safety.
However, a majority of connected worker platforms overlook the fact that connectivity doesn’t end with simply linking workers to their platform. They fail to recognize the immense benefits that live connections to enterprise systems of record bring to frontline business processes and activities.
Manufacturing success hinges on the seamless integration of connected worker platforms with legacy and enterprise systems to provide adequate support to frontline workers, giving them access to data and knowledge that can boost their efficiency and keep them safe.
Read below for more information on connected worker platform integrations; what they entail, which enterprise systems are essential for integration, and how AI-powered technology improves impact on frontline manufacturing activities.
Connected Worker Integrations: More than just an API
In manufacturing, it is critical that connected worker platforms are integrated with various enterprise systems to streamline operations and ensure that workers have the data and information they need at their fingertips. As critical as this is, most connected worker vendors believe that providing an open API is sufficient, and even boast that they integrate to enterprise systems, when in fact they place this burden on their customers.
Having an API is not enough
There are several not-so-obvious aspects to connected worker platform integrations, including:
Connected worker integrations with enterprise applications, even streamlined ones, have essential requirements such as logic that needs to be written, customized, run, and supported. Most, if not all, of this logic is initiated by the connected worker platform, propagating events and data from shop floor processes to the associated enterprise system of record.
Connected worker platforms with just an “API” require all of this functionality to be developed, hosted, and supported externally. The responsibility is then on the customer to build a custom product and select and support the hosting environment. This effort (building, hosting, and support) can cost between $50K and $150K to build and test, and then another $50K – $150K annually for 5 x 9 support. And, the customer is responsible for maintaining an SLA acceptable to the business (99.9% being typical).
Pro Tip
It’s critical that connected worker platforms include “platform-as-a-service” (Paas) capabilities that provide the ability to write, support, and execute both standard and custom integrations. These can be done by the platform provider, the customer, as well as third-party system vendors and system integrators. Providing PaaS capabilities puts the responsibility on the vendor for operating the integration service, and maintaining SLAs, geo-redundancy, disaster recovery, and privacy and security. In short, just saying “we have an API” places an undue burden on customers, and prevents building the sustainable connected enterprise necessary to remain competitive in today’s global economy.
Which Enterprise Systems Should You Integrate
In any industrial environment, connected worker platforms should be integrated with various systems to support operations, help with cooperation and communication, and gain valuable insights into frontline manufacturing processes. These integrations streamline activities, improve efficiency, and provide a unified digital environment that empowers frontline workers.
This concept of a connected enterprise spans several initiatives within an organization: assets and equipment, the products being manufactured, the end customer, operations, workers, and the entire supply chain, and is highlighted below using the Industrial Transformation (IX) Reference Architecture from LNS Research.
Examples of enterprise management systems of record that are key to connected worker success and should be integrated are:
ERP (Enterprise Resource Planning)
EAM (Enterprise Asset Management)
HCM (Human Capital Management)
HR, Training, and LMS (Learning Management System)
QMS (Quality Management Systems)
MES (Manufacturing Execution System)
CMMS (Computerized Maintenance Management System)
Supply Chain Management
Enterprise systems such as ETQ, Workday, UKG, SAP, Oracle, IBM Maximo, Microsoft Dynamics 365, Salesforce, and ADP provide transformational value for a manufacturing company if they can be connected into frontline operations. By integrating connected worker platforms with these systems, manufacturers can create an interconnected environment that supports frontline workers and drives operational excellence. Ultimately, integration enhances collaboration, workforce visibility, decision-making processes, and overall operational efficiency, making connected worker platforms an indispensable component for manufacturing organizations.
Improving Integration Success Through Augmentir
At Augmentir, we see integrations differently than other connected worker platforms. Our rich history of building integrations in the manufacturing space enabled us to design a connected worker solution that easily, bi-directionally, and securely integrates the enterprise systems of record to create closed loop processes involving the frontline workforce.
Augmentir has internal PaaS services to run connectors that we build and support for popular enterprise applications like SAP, Salesforce, ETQ, Oracle, IBM Maximo, and more. Additionally, our PaaS enables custom integrations to be built and executed for custom, and niche applications. All third-party integrations running in the Augmentir connected worker platform carry the same SLA and geo-redundant support. By facilitating connected worker platform integrations with enterprise systems in this way, we have provided leading manufacturers with increased workforce visibility, improved productivity, digitized and standardized processes, enhanced training and collaboration, and more.
Furthermore, because we are the leading AI-powered connected worker provider, we have brought innovative generative AI technologies such as AI-driven analytics, machine learning algorithms, NLP, predictive maintenance, and industrial AI copilots to improve connected worker integrations with enterprise systems, providing real-time guidance, enabling predictive analysis, and enhancing communication and collaboration among workers.
Schedule a demo to learn more about our AI-powered connected worker solutions and how they are drastically improving frontline processes, training, and manufacturing activities.
Say hello to the newest addition to the Augmentir platform, Augie – the GenAI powered digital assistant for manufacturing.
Say hello to the future of work in manufacturing with the latest addition to Augmentir’s suite of connected worker tools, Augie™.
Augie is a digital assistant for frontline operations that utilizes Generative AI and proprietary fit-for-purpose, pre-trained Large Language Models (LLMs) to enhance operational efficiency, problem-solving, and decision-making for today’s less experienced frontline industrial workers. It leverages enterprise-wide data, provides instant access to relevant information, closes skills gaps with personalized support, offers insights into standard work and skills inventory, and identifies opportunities for continuous improvement.
Augie is a result of our dedication to empowering frontline workers, leveraging AI to support manufacturing operations, and giving manufacturing workers better tools to do their jobs safely and more efficiently.
Continue reading below to learn more about how Augie works and how it can benefit your frontline workforce and manufacturing operations:
Generative AI-powered smart manufacturing assistants are designed to provide secure, role-based, personalized assistance to frontline workers, engineers, and managers in various industries, including manufacturing.
They work by leveraging artificial intelligence and integrations across different software systems, providing guidance and assistance in various tasks to enhance productivity and performance. This includes providing data insights, recommendations on actions to improve performance, and the ability to create analyses and dashboards with a natural language-based assistant.
A majority of smart manufacturing assistants only draw their information from manufacturing execution systems (MES), without tying in other important systems necessary for frontline manufacturing success.
Augie, however, is different. It leverages enterprise-wide data tying in information from a wide range of platforms including operational data, training and workforce management data, connected worker and engineering data, as well as information from enterprise systems.
How Augie Benefits Your Frontline Workforce
Augie is unique among other smart manufacturing assistants. It leverages proprietary fit-for-purpose, pre-trained LLMs and generative AI, coupled with robust security and permissions, to help factory managers, operators, and engineers improve efficiency, resolve issues faster, and prevent downtime.
With information readily available via Augie, frontline workers can make decisions faster, reduce downtime, and improve troubleshooting with instant access to summarized facts relevant to a job or task. Additionally, Augie is multi-modal, meaning it can return actionable information in the form of work procedures, training videos, recorded collaborations, engineering documents and SOPs, as well as tribal knowledge.
Through Augie, manufacturers can instantly:
Close skills and experience gaps with personalized support
Gain insights into Leader Standard Work
Gain new insights into skills inventories
Convert Tribal Knowledge into Digital Corporate Assets
Identify opportunities for continuous improvement
Forecast potential operational issues
With Augie by your side, you can streamline manufacturing operations, optimize performance, empower your frontline workforces, and stay ahead in today’s rapidly evolving and competitive landscape.
Improve Operational Efficiency with Augie and Augmentir
The digitization of frontline processes has become a must-have to keep up with the velocity of change – but not just digitization … smart digitization. Recently, Deloitte found that 86% of manufacturing executives believe smart factory solutions will be the primary drivers of competitiveness in the next five years. Leveraging smart, AI-driven connected worker solutions that allow industrial organizations to best support their frontline workforces and optimize processes to make them safer and more efficient is critical to overall enterprise success.
At Augmentir, we have been met with continued success in our efforts to transform manufacturing operations. Our patented Smart AI foundation helps manufacturing organizations close the loop between training and work execution, delivering the data and in-line insights necessary to continuously improve operational excellence day-over-day, year-over-year. Augmentir is the world’s leading connected worker solution, combining smart connected worker and GenAI technologies to drive continuous improvement and enhance performance management initiatives in manufacturing.
The addition of Augie to our platform is a game-changer for factory floor and other frontline workers, allowing for quick reference troubleshooting and useful, contextualized information to be delivered at the moment of need. Furthermore, with Augie, less experienced workers are provided with additional support and individualized guidance based on the job or task needs.
With patented AI-driven insights that digitize and optimize manufacturing workflows, training and development, workforce allocation, and operational excellence, Augmentir is trusted by manufacturing leaders as a digital transformation partner delivering measurable results across operations. Schedule a live demo today to learn more.
The evolution of AI in manufacturing has seen tremendous growth over the past few decades, now becoming more adaptive and collaborative, and being used to augment and directly support frontline workers.
The evolution of artificial intelligence and machine learning technologies in manufacturing has seen tremendous growth over the past few decades, with astounding leaps in technology and industry-wide transformations.
Dating back to the 1960’s, manufacturers started using AI in robotics and basic automation. This early usage focused on automating manual, highly repetitive human tasks such as assembly, parts handling, and sorting, allowing for higher levels of production and efficiency.
Over time, this evolved with AI-enabled machine vision systems, which were used to automate visual inspections, allowing for better quality control and precision during production cycles. More recently, AI has been at the center of warehouse automation, as well as the Industrial Internet of Things (IIoT), where physical machines and equipment are embedded with sensors and other technology for the purpose of connecting and exchanging data, which is used in predictive analytics for machine health monitoring. Manufacturers can now glean valuable insights from data collected over time about optimizing their operations for maximum efficiency without sacrificing quality.
Despite the breath of applications that AI has in the industrial setting, there is a common thread across all of the above examples – AI has largely been used to automate highly repetitive or manual tasks, or perform functions designed to replace the human worker.
However, these examples laid the groundwork for the adoption of AI in manufacturing and for the use of AI technologies that augment and directly support frontline workers today.
Read below for more information on how the use of AI and GenAI is evolving in manufacturing, and being used to augment the human worker, transforming productivity and efficiency at a time when workforce optimization is needed most.
Using AI to Augment, not Replace the Workers in our Factories
Today, AI technologies in manufacturing have evolved to encompass a diverse range of applications. According to Deloitte, 86% of surveyed manufacturing executives believe that AI-based factory solutions will be the primary drivers of competitiveness in the next five years. Robotics and automation have become more adaptive and collaborative, working alongside and augmenting human workers to streamline production processes and increase efficiency – rather than simply trying to replace them.
As computing power and algorithmic capabilities improved, AI in manufacturing has become more advanced and widespread. The emergence of Industry 4.0, characterized by the convergence of digital technologies, further accelerated AI’s role in manufacturing. By leveraging tools like connected worker solutions to gather frontline data, manufacturing organizations can now capitalize on AI’s extraordinary computing power to analyze that data and derive actionable insights, improved processes, and more.
Much like the industry has learned to optimize equipment from the 1.7 Petabytes of connected machine data that is being collected yearly, we are now able to optimize frontline work processes and people from highly granular connected worker data, with one major caveat: In order to leverage this incredibly noisy data, a system has to be designed with an AI-first strategy, where the streaming and processing of this data is intrinsic to the platform – not added as an afterthought.
The potential for AI to help augment the human worker is there, but why now?
Because for today’s manufacturers, time is not on your side.
The workforce crisis in manufacturing is accelerating, and at the forefront of the minds of Operations and HR leaders. Job quitting is up, tenure rates are down, and manufacturers struggle daily to find the skilled staff necessary to meet production and quality goals. The threat is huge – with significant impacts to safety, quality, and productivity.
AI-based connected worker solutions allow industrial companies to digitize and optimize processes that support frontline workers from “hire to retire”. These solutions leverage data from your connected workforce to optimize training investments and proactively support workers on the job, across a range of manufacturing use cases.
Furthermore, solutions that leverage Generative AI and proprietary fit-for-purpose, pre-trained Large Language Models (LLMs) can enhance operational efficiency, problem-solving, and decision-making for today’s less experienced frontline industrial workers. Generative AI assistants can leverage enterprise-wide data, provides instant access to relevant information, closes skills gaps with personalized support, offers insights into standard work and skills inventory, and identifies opportunities for continuous improvement.
Augmentir’s AI-First Journey
At Augmentir, since the beginning, we pioneered an AI-first approach toward manufacturing and connected frontline worker support.
Many manufacturing solutions incorporated AI technology as an add-on or afterthought as the technology gained more advanced capabilities and popularity. We, however, have been championing and building a suite of solutions using AI as a foundation. Our platform was designed from the bottom up with AI capabilities in mind, placing us as a leader in the connected frontline worker field.
2019 – Augmentir launched the world’s first AI-first connected platform for manufacturing work empowering frontline workers to perform their jobs with higher quality and increased productivity while driving continuous improvement across the organization. This marked the start of our AI-first journey, giving industrial organizations the ability to digitize human-centric work processes into fully augmented procedures, providing interactive guidance, on-demand training, and remote expert support to improve productivity and quality.
2020 – Augmentir unveiled True Opportunity™, the first AI-based workforce metric designed to help improve operational outcomes and frontline worker productivity through our proprietary machine learning algorithms. These algorithms take in frontline worker data, then combine it with other Augmentir and enterprise data to uncover and rank the largest capturable opportunities and then predict the effort required to capture them.
2021 – Building on user feedback and field data, Augmentir reveals True Opportunity 2.0™, with improved and enhanced capabilities surrounding workforce development, quantification of work processes, benchmarking, and proficiency. By Leveraging anonymized data from millions of job executions to significantly improve and expand the platform’s ability and automatically deliver in-app AI insights we were able to increase benefits and returns for Augmentir customers.
2022 – Augmentir announces the release of True Productivity™ and True Performance™. True Productivity allows industrial organizations to stack rank their largest productivity opportunities across all work processes to focus continuous improvement teams at the highest ROI and True Performance determines the proficiency of every worker at every task or skill enabling truly personalized workforce development investments.
2023 – Augmentir launches Augie™ – the GenAI-powered assistant for industrial work. By incorporating the foundational technology underpinning generative AI tools like ChatGPT, we enhanced our already robust offering of AI insights and analytics. Augie adds to this, improving operational efficiency and supporting today’s less experienced frontline workforce through faster problem-solving, proactive insights, and enhanced decision-making.
2024 – As this year progresses, we have already continued to refine our AI-first solutions and apply user feedback and additional features to best support frontline industrial activities and workers everywhere.
2025 and beyond – True Engagement™, looking forward we predict the evolution of AI in manufacturing activities will continue, progressing until we can accurately measure signals to detect the actual engagement of industrial workers and derive useful information and insights to further enhance both HR and manufacturing processes.
We are deeply involved in applying AI and emerging technologies to manufacturing activities to augment frontline workers, not replace them. Providing enhanced support, access to key knowledge (when and where it does the most good), and improving overall operational efficiency and productivity.
The Future of AI in Manufacturing – The Journey Forward
As we press onward into the future, we at Augmentir are determined to champion the application of AI and smart manufacturing to augment and enhance frontline workers and industrial processes. We will continue to evolve our application of AI and its use cases in manufacturing to help frontline teams and workforces, reinforcing our AI-first pedigree.
The addition of Augie to our existing AI-powered connected worker solution is an important step forward. Augie is a Generative AI assistant that uses enterprise-wide data, provides instant access to relevant information, closes skills gaps with personalized support, offers insights into standard work and skills inventory, and identifies opportunities for continuous improvement. Augie is a result of our dedication to empowering frontline workers, leveraging AI to support manufacturing operations, and giving manufacturing workers better tools to do their jobs safely and more efficiently.
With patented AI-driven insights that digitize and optimize manufacturing workflows, training and development, workforce allocation, and operational excellence, Augmentir is trusted by manufacturing leaders as a digital transformation partner delivering measurable results across operations. Schedule a live demo today to learn more.
https://www.augmentir.com/wp-content/uploads/2024/03/evolution-of-ai-in-manufacturing.webp6301200Chris Kuntzhttps://www.augmentir.com/wp-content/uploads/2021/09/Augmentir_Logo_Sm-300x169.pngChris Kuntz2024-03-23 02:00:412024-06-04 11:38:07The Evolution of AI in Manufacturing
