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Digitalization in Oil & Gas by the Numbers

Growth Prospects

  • The global upstream industry will invest over $500 billion and generate over $800 billion in free cash flows in 2024. (3)

  • 81X The increase in unconventional oil and gas productivity due to technology over the last decade. (6)

  • 60% of oil and gas executives expect digital technologies and AI to change their businesses significantly by 2030. (2)

  • $5 per barrel of oil equivalent (BOE) captured for upstream companies through digitalization initiatives in exploration, well management and maintenance. (1)

Workforce Challenges

Oil and gas companies in North America are having difficulty finding frontline workers. (2)

the percentage of the existing workforce in oil and gas that is expected to retire within the next 7 years. (5)

of oil and gas executives say reskilling the workforce will be critical to company success going forward. (6)

Energy Transition

oil and gas executives cite operational efficiency gains and direct emissions reductions as key metrics for assessing energy transition progress. (3)


oil and gas executives look to adjacent products such as natural gas, carbon capture, biofuels and hydrogen as key to their low-carbon investment strategies.


oil and gas executives say digital technologies to improve efficiency are among their top investments for decarbonization initiatives. (7)


Supporting Data

  1. McKinsey:  Technology Transformation in Oil and Gas
  2. Bain: Global Energy and Natural Resources Executive Perspectives
  3. Deloitte: 2024 Oil and Gas Industry Outlook
  4. Statista: AI impact on U.S. oil and gas company staff 
  5. The Economic Times
  6. Ernst & Young
  7. Deloitte: Navigating Energy Transition
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Keys to Achieving Workforce GMP Compliance

Good Manufacturing Practices (GMP) are an essential foundation for successful manufacturing companies. To uphold these practices effectively, companies must establish robust systems and procedures. Among the critical elements of GMP is ensuring and validating workforce compliance with established policies. However, the implementation of these validation processes often comes with significant challenges for manufacturers. 

Building on a Solid Foundation

A major focus for quality management professionals is the creation, approval and maintenance of policies and procedures for GMP. Comprehensive documentation is vital for GMP compliance. Developing detailed Standard Operating Procedures (SOPs) is a cornerstone of GMP best practices, but the foundation for GMP documentation extends across all aspects of the company.

From company quality goals to full assessments of risks and responses to the development and production of products to guidelines for suppliers and commitments to customers, all procedures and processes should be well-documented. This documentation is critical to implementing GMP and serves as an important level of evidence of compliance, but GMP compliance is not just about written procedures. Compliance depends on the practical implementation of those procedures in daily operations.

Top Challenges of Workforce GMP Compliance

Even with the most thorough documentation, consistent GMP compliance can be difficult to achieve and maintain. Manufacturers must manage the interaction of people, production, equipment, facilities, suppliers and customers and the ripple effect of any changes. Regular maintenance and calibration of systems, facilities, and equipment are imperative for GMP compliance, along with supplier audits and ongoing customer feedback. However, supporting and validating workforce compliance poses certain unique challenges that are often difficult to address for manufacturers.

Developing and Validating Job Competence

One of the primary challenges in workforce GMP compliance is ensuring that all employees are adequately trained and aware of GMP policies. Training programs should ensure all personnel understand their roles in maintaining GMP standards. Too often, training is considered a job-shadowing experience, or solely an onboarding activity, which may not adequately support GMP success.  And, employee turnover, experienced workers retiring, or the introduction of new staff can degrade GMP compliance practices as well. 

Regular communication updates should be utilized to keep employees continuously informed about changes in procedures, regulations, and industry best practices.  Refresher courses, and on-the-job, interactive training methods can help maintain a well-informed workforce. It is also essential to verify the completion of training programs and the practical application of GMP principles in daily tasks. Implementing competency assessments, layered process audits (LPA) and conducting periodic skill evaluations in real-world scenarios are vital steps in validating workforce compliance

Enforcing and Validating SOPs

The existence of SOPs is not enough; they must be actively enforced and implemented. Beyond training frontline workers, a framework to ensure adherence to the SOPs is what can deliver the best outcomes. Regular monitoring and supervision are essential to verify compliance, and any deviations should be promptly addressed through corrective actions. In addition, it is important to look for differences between locations, teams or shifts, across processes and at handoffs. Variations in procedures and practices may lead to compliance gaps

Along with enforcement comes the companion requirement for regular validation of SOPs to confirm that they are both effective and in compliance with GMP standards. This involves assessing the outcomes of processes, identifying any deviations, and implementing corrective actions. Continuous improvement is key, and feedback from the workforce, suppliers and customers should be considered in the validation process.

Integrating GMP into Every Process

Quality should not be an afterthought, but an integral part of the workflow on the frontline. Workforce tasks at each stage of the manufacturing process should prioritize GMP. This is particularly challenging given that the typical manufacturing workforce operates in a world of paper SOPs and training. With the advances in digital tools, manufacturers should seek out ways to modernize their frontline workers’ access to digital guidance and information that assists adherence to SOPs and GMP processes. 

 Frontline workers should also be empowered to identify and address issues that may compromise GMP. Here again, modern digital tools can enhance workforce abilities to both spot and communicate issues as they arise. These tools can also incorporate on-the-spot guidance and micro-training to ensure adherence to GMP. In addition, integrating GMP into the daily workflow of frontline workers promotes a culture of continuous improvement and accountability.

After All the Planning, it Depends on People

In addition to equipment and processes, manufacturing is powered by people. The workforce plays a pivotal role in GMP compliance, but resistance to change or lack of employee engagement can impede compliance efforts. Manufacturers can address this challenge by fostering a culture of GMP ownership, recognizing, and rewarding compliance efforts, and involving workers in the decision-making processes related to GMP policies.

The workforce may view GMP compliance as an additional burden in the production process. Not only does this challenge manifest itself in the continuity of training, but also in tasks directly related to GMP compliance validations. Language and cultural differences may introduce additional obstacles. The key is to simplify and streamline compliance practices, considering the time and effort required by the workforce as partners in the delivery of GMP.

Taking  a Digital Approach to Ensure Workforce GMP Compliance

While the journey toward workforce GMP compliance has many challenges, manufacturers can overcome these obstacles with thorough planning and proactive approaches that facilitate workforce adoption of GMP policies. Modern digital platforms specifically designed for frontline workers, like ROO.AI, deliver a significant boost for workforce GMP compliance. 

ROO.AI’s advanced visualizations simplify and speed up inspections, safety checks, equipment maintenance, and LPA and other GMP audits while making it more visually intuitive to adhere to GMP standard operating procedures. Automating the data capture for GMP validation process also reduces time and effort for workers, addressing the resistance that additional quality steps may face from the workforce. Digitalizing the frontline empowers workers to be more proactive about identifying potential quality issues and communicating with their team and managers to make improvements. With ROO.AI, work instruction with access to micro-training can be accessed on-the-spot, training courses and updates delivered directly to workers as tasks, and completions and certifications tracked to ensure workforce job competency.

Ensuring workforce compliance with GMP is a multifaceted process that requires a comprehensive approach. By creating robust SOPs, enforcing and implementing them effectively, documenting processes meticulously, validating procedures regularly, and combining these efforts with a frontline digital platform to ensure understanding, adherence and accountability, manufacturers can prioritize quality at every stage of the manufacturing process to establish a strong foundation for GMP compliance. 

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Improving Training and Safety for Frontline Workers in Oil Field Services

With the exposure to a wide variety of equipment and the dynamic, complex nature of oil field services operations, companies in the oil and gas industry have historically faced challenges in ensuring the well-being and competence of their frontline workforce. Frontline operator positions in the oil and gas industry are considered the third most dangerous of all frontline positions. With the ongoing departures of experienced personnel, oil field services companies are faced with a critical challenge in training and ensuring compliance with safety procedures as they replenish the frontline workforce.

In recent years, however, the adoption of digital technologies offers an unprecedented opportunity to enhance frontline worker training methodologies and safety protocols. A Draeger Safety study showed that using eLearning technologies reduced reported safety incidents by 46%. Advances in digital technologies such as virtual reality (VR), augmented reality (AR), wearables, AI and data analytics offer oil field services companies a transformative opportunity to develop a safer and more productive connected workforce with digitalized work instruction, inspections, safety and procedural training.

Revolutionizing Training with Digital Technologies

Digital Technologies are fundamentally changing training in several ways. One of the most significant advancements in training for frontline workers in oil field services comes from the ability of modern digital technologies to immerse the worker in the training content visually. Virtual reality (VR), in particular, places workers in simulated environments that replicate real-world equipment and operations. With virtual reality, workers can more effectively experience complex tasks and hazardous conditions to refine their skills in a risk-free environment.

In contrast, augmented reality (AR) overlays digital information into the physical world. This technology proves beneficial for on-the-job training, allowing workers to access relevant data and instructions while performing tasks. While both VR and AR are in the early phases and still quite expensive, innovative visualization technologies on standard mobile devices are also available. 

These new lower-cost approaches combine the benefits of mobile, on-the-spot training with highly visual representations of information that are more easily and quickly understood and can be embedded into standard work instructions to provide ongoing reminders.  These digital advances contribute to more effective and engaging training, ensuring that frontline workers are better prepared to navigate the challenges they may face in the field.

Tailoring Training with Data and Analytics

Digital technologies also enable the customization of training, addressing specific job roles and operational contexts. Data and analytics play a pivotal role in this customization process by adapting training to the specific needs of the operator and analyzing historical data to identify patterns and trends. 

Furthermore, ongoing data analysis allows for continuous improvement in training methodologies. By monitoring workers’ performance metrics using digitalized SOPs, inspections and maintenance work orders, oil field services companies can identify areas that may require additional training or support, leading to a proactive approach to addressing potential safety and operational issues. This iterative process ensures that training programs remain dynamic and responsive to the evolving needs of frontline workers.

Interactive, Micro-learning Delivery

Digital technologies facilitate a shift from traditional, classroom-style training to interactive and micro-learning delivery of training. Through immersive simulations, workers can experience realistic scenarios and practice decision-making under pressure. This type of interactive training proves invaluable in preparing frontline workers for the unpredictable nature of oil field operations.

Mobile digital technologies also change the script of classroom training by providing training at the point of need in small, specific installments. Referred to as micro-learning, this approach has been documented to be 5-10 times more effective than conventional training with retention rates up to 60% higher. By digitalizing work instructions and inspections typically used by frontline workers, oil field services companies can embed safety and process training opportunities into the work processes not only facilitating access to the training but also ensuring and monitoring delivery and consumption.

Real-Time Monitoring and Wearable Devices

In addition to transforming training, digital technologies can also offer real-time monitoring capabilities through the deployment of wearable devices and sensors. These devices track various metrics, including workers’ health and environmental conditions, or locations and proximity to hazards.

Real-time monitoring enables immediate response to emergencies, ensuring that frontline workers receive timely assistance in the event of accidents. Wearable devices are also used as a preventive measure to alert workers and supervisors to potential hazards based on real-time data, allowing for proactive risk mitigation.

Making the Transition Accessible, Affordable and Effective

Oil Field Services companies have a growing number of digital alternatives they can leverage to improve safety and operational efficiency for their frontline workforce. ROO.AI is partnering with oil field services companies to digitalize common, critically important frontline processes such as field maintenance, rig up and rig down operations, equipment and site safety checks, and equipment repair and return to service. By enabling the concepts discussed, such as visualization, personalization and microlearning, ROO.AI is helping innovative companies in the oil and gas industry to upskill the workforce and cultivate a culture of safety. Applying digital technologies like ROO.AI ensures that frontline workers are not only well-trained but also equipped with the tools and knowledge needed to navigate the complexities of oil field services efficiently and safely.

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Key Frontline Metrics That Boost Production Quality

Frontline workers are the foundation of many manufacturing companies’ production process, and their activity is crucial in enhancing product quality. The precision and accountability of the frontline workforce directly influence production quality, making it essential to establish and monitor key quality metrics.

 In addition, recent studies like one by the American Quality and Productivity Center (APQC) highlighted that reducing rework and scrap could add back over 2% to manufacturer’s profitability.  Data like this creates a further incentive for quality management programs to look for ways to expand their impact on the frontline. Recognizing the critical role of frontline workers in shaping production quality is the first step toward implementing a comprehensive quality management system.

To achieve this, it is essential to track and measure specific frontline quality metrics that directly impact production quality. Furthermore, making these metrics clear and visible to the frontline workforce enables workers to participate in the effort to drive higher quality. This is a critical element of an effective Quality Metrics program. A Deloitte study found that metrics that create the impression of tracking worker activities were perceived by 15% of workers as demotivating, and the same study found that as much as 32% of worker time shifted to performative work that just gave the impression of productivity.

Engaging workers in the selection and measurement of quality metrics can deliver a much more effective program that will be more widely adopted and supported by the frontline workforce. While the emphasis and focus of these metrics might vary in relation to the products and manufacturing processes of a specific manufacturer, the core concepts at the foundation of these metrics are very relevant to frontline activities across industries.

First Pass Yield

Measuring the percentage of products manufactured correctly without the need for rework or repair is a critical metric for frontline operations. The metric sheds light on whether production processes are efficiently and consistently delivering quality outputs. Monitoring First Pass Yield  enables manufacturers to identify areas of improvement in their processes, machinery, or workforce training, ensuring that products meet quality standards from the outset.

Defect Rate

While First Pass Yield measures the relationship between efficiency and quality, Defect Rate measures the overall quality levels of the production process. Monitoring and minimizing defect rates are paramount in ensuring customer satisfaction, reducing production costs associated with rework or scrap, and maintaining high levels of product quality. A lower defect rate signifies a higher level of precision and consistency across all aspects of production, contributing to the overall excellence of manufactured products. 

Scrap and Rework Rate

Understanding the scrap and rework rates provides visibility into the costs of poor quality, as well as, visibility into many aspects of the manufacturing process. Tracking this metric helps manufacturers to identify defect trends and look for the root causes of defects, allowing for targeted improvements in processes, materials, or training to minimize waste and enhance overall quality.

Schedule Realization

Schedule realization measures the ability of a manufacturing facility to meet schedule or delivery goals which in turn directly impacts quality by meeting customer expectations. High schedule realization rates indicate that the production schedule is being effectively managed, contributing to overall operational efficiency and quality..

Tracking Employee Training and Certification Rates

Ensuring the continuous training and certification of frontline employees is essential for maintaining and improving production quality. Well-trained workers not only make fewer errors, but they are also more adept at spotting potential issues that can affect quality. Providing regular training opportunities ensures that employees stay current with critical skills used on the frontline and the current manufacturing processes that the company has set as standards. A skilled and knowledgeable workforce is a cornerstone of high-quality.

Key Steps For Success

Engaging the frontline in the program is a key to success. Tap frontline supervisors and visible leaders in the workforce to help define the program, while using the opportunity to discuss the importance of setting measurable quality goals for frontline workers. Emphasize the value of establishing current state baselines and benchmarking against industry standards or best practices. This also offers an opportunity to set targets with buy-in from the frontline workforce.

Equally critical to success is the ability to ensure standardized inspection processes and to quickly and easily capture the required data. Introduce tools and technology that will simplify the process for the frontline to ensure adoption and consistent use. Platforms such as ROO.AI are critical in guiding workers through standardized inspections and automating collection of data so that quality metrics programs for the frontline are not perceived as slowing production or creating unnecessary work.

Finally, use the initiative to provide the frontline workforce with the opportunity to contribute to continuous improvement efforts that boost quality. Provide visibility of quality metrics to frontline workers and build into the process, preferably within the digital platforms, an easy way to suggest improvements or identify possible root causes of quality issues. Make these contributions visible across the workforce, potentially with recognition and rewards, to increase worker engagement. Utilizing program design and launch to reinforce training initiatives for frontline workers is also an opportunity not to be missed.

Informed Workers Are A Key To Quality

Frontline workers are the driving force behind production quality, and the implementation of key quality metrics can help them make informed decisions and drive continuous improvement. By embracing frontline quality metrics and implementing enabling digital platforms for quality inspections and data collection,  manufacturers can empower their frontline workforce to enhance production quality, reduce defects, and deliver products that meet and exceed customer expectations. This approach not only results in higher customer satisfaction but also boosts efficiency, productivity and competitiveness in the market.

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Innovator in Flowback and Sand Management Innovates the Frontline

EnerCorp is a leading provider of engineered solutions for the oil and gas industry.

Known for its innovations in eFlowback and Sand Management equipment, EnerCorp infuses innovation into every aspect of the company, driving to deliver better, faster, more effective approaches in technology, safety, operations and customer service.

Modernizing Pre and Post Job Inspections

With competition and costs increasing, the company was looking for modernization opportunities. EnerCorp’s innovative equipment was in high demand, and enabling accurate visibility to equipment inventory was a key to maximizing revenue opportunities across operating locations. Fast and efficient equipment turn-round was also a pivotal factor in meeting customer demand and increasing EnerCorp’s return on capital. Ensuring maintenance crews were able to consistently identify and document the condition of equipment post job was critical to EnerCorp’s ability to chargeback needed repairs to customers which would improve operating margins.

Looking for a frontline-optimized solution

EnerCorp’s team had already leveraged computerized solutions for the management of the equipment used to deliver services to their customers, but the team led by Aaron Kelver, US Asset Manager, was always on the lookout for opportunities to innovate. Aaron wanted to streamline the processes of pre and post job inspections which at the time was done with a system that was more appropriate for office workers. Rather than force frontline workers or supervisors to document the inspection in an office, after the fact, Aaron wanted to use mobile devices to digitalize the process and capture data and images on the spot. The goal was to make the system more efficient and frontline-friendly while building in standardization and training which the old system did not provide.

Live inside 90 days

EnerCorp set an ambitious target of replacing the existing software within 90 days. The team partnered with ROO.AI to model the equipment management system, the inspections, and the repair workflows for their high-volume Sahara Sand Separators. With a working framework, the project was expanded to the rest of the EnerCorp equipment inventory. Using ROO.AI’s agile implementation approach and the platform’s ability to make quick changes immediately available, Aaron’s team delivered a frontline-optimized solution across their eFlowback and Sand Separator product lines within 90 days.

  • Mobile Pre and Post Job Inspections with embedded micro-training that reinforced standard operating procedures
  • A cloud-based equipment management system that aggregated detailed information, documents, images, and recertification renewals while dynamically attaching every inspection for each unique asset
  • Equipment transfers workflows and asset inventory reporting by status and location with data downloading to CSV for additional analysis
  • Automatic generation of customer-ready documents with details and images from inspections and the automated collection and calculation of repair costs and labor hours

Gathering the data to better drive the business

With ROO.AI, EnerCorp’s frontline staff can use their mobile devices as they conduct inspections and repairs to document issues and verify equipment conditions. The standardized process is enforced through the ROO.AI app while data collection and report generation is automated to improve efficiency and accuracy. Equipment status and location are now immediately visible. With ROO.AI in place, Aaron is seeing more opportunities to use the data to identify preventable issues and understand the real costs of maintenance and repairs to help reduce equipment downtime, lower maintenance expenses, and improve return on capital. 

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Digital Logistics Gains Momentum

Transportation and logistics providers continue to face challenges with labor and skills shortages and managing costs. A recent study published by McKinsey that surveyed 250 logistics leaders in transportation and warehousing found that the companies were not only turning to digital technologies to address these challenges but were increasing investments in advanced logistics solutions to address digitalization beyond traditional transportation management and warehouse management solutions.

“Together, the survey findings suggest that if a company isn’t reimagining the way it works in conjunction with technology—all while building newer breakthrough capabilities—achieving the expected ROI from technology commitments may become harder than ever.”

McKinsey

Advanced digitalization initiatives for logistics operations span the gamut from robotics and fully automated picking, drones and delivery vehicles, to digital twins, to real-time tracking and route optimizations. And as broad as the digital initiatives are, so are the differences in their readiness for actual wide-scale adoption across the industry. Many of these technologies are in the early stages of development, but there are some important new digital solutions currently available that can transform critical logistics operations in areas such as fleet management and warehouse and distribution center operations.

Reimagining frontline operations looms large in the possibilities for transportation and logistics providers. The survey highlights the top concerns for the companies as Labor Management, Productivity and Cost Management. All critical challenges that are directly affected by the frontline workforce skills gaps and labor shortages. Fortunately for logistics providers, frontline digital technologies are readily available, easy to adopt and very cost-effective. Solutions like ROO.AI can deliver swift time to impact with little investment in time or resources from the logistics provider.

Apply Digital to Top Logistics Concerns

In an industry that is still highly dependent on a frontline workforce, digital tools can make a tremendous impact in the key areas highlighted in the McKinsey survey. Labor Management challenges due to shortages and skills gaps can be improved by providing workers with digital tools for easier access to orientation, training and safety guidelines to accelerate onboarding. In addition, 60% of workers from an eduMe survey reported that they were unhappy with the technologies they used at work, and one-third of frontline workers in a Microsoft study felt they did not have the right digital tools to do their jobs effectively. Digital frontline tools can not only improve onboarding but can also help attract and retain skilled workers.

Increasing productivity on the frontline is often dependent on upskilling workers and ensuring that they can move quickly through standardized fleet and warehouse operation processes. Frontline digital solutions like ROO.AI improve efficiency by replacing paper for instruction and data collection. ROO.AI customers see reductions in process times by up to 70% due to the visual guidance and automation of data collection.

Aside from improving productivity, which is a direct input to managing costs, digitalizing frontline operations with ROO.AI drives greater accountability for quality, which can reduce rework and mistakes that cause delays and add to overall costs. In addition, ROO.AI customers leverage their digital frontline platforms for risk mitigation, capturing digital proof for all shipments and logistics activities, providing easily accessible audit trails to address any customer claims.

As the McKinsey study points out, digital logistics is being overwhelmingly endorsed across the industry. However, it is equally important that companies combine that momentum with reimagining their operations. Across the board, frontline workers play a critical role in logistics operations, and the digitalization of the processes they drive is one of the areas where easily available, readily implementable digital solutions exist today.

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How Digitalizing Frontline Data Boosts Oil Field Service Profitability

Like most industries, oil field service companies have invested in digitalizing the back-office and leveraging the data to drive better visibility and decision making. In the field and on the frontline, digitalization is just starting. Paper is the most common system for ticketing, equipment maintenance, field inspections and safety checks which leaves that data trapped in paper silos. Companies are collecting their frontline data; they just can’t effectively use it. To add to these challenges, a recent Microsoft survey of the Energy industry showed that nearly a third of frontline workers feel that they do not have the digital tools they need to do their jobs effectively.

Using Digital Data to Improve Field Operations

With the attrition of experienced workers and labor shortages, digitalizing frontline operations offers a real advantage. In addition to guiding workers and offering on the spot training, digitalizing the frontline can also deliver data to improve operational efficiency. Usage data from digital workflows can provide visibility into the execution of frontline activities. OFS companies can track missed inspections, maintenance and safety checks to ensure compliance. Data from operations can also be used to compare performance across teams and to measure turn-around times for asset maintenance, creating opportunities for training and improvement.

Boosting Cost Recovery with Digital Data

A common challenge for OFS companies is recovering the costs of excessive wear on assets that occur on the job. Digitalizing asset inspection and repair operations can provide the basis for cost recovery programs using the data to more accurately assess cost of usage and also deliver evidence to customers for the recovery of wear and damage charges. This data becomes particularly effective when utilizing modern digital frontline capabilities for images and video records.

Reducing The Costs of Inventory Management

Eliminating frontline paper silos and connecting workers delivers a stream of data that can greatly improve inventory management and reduce costs. Digitalizing the frontline provides a more accurate and timely view into the actual usage trends for equipment and replacement parts, enabling asset managers to more effectively purchase and allocate parts inventory needed to match operational demands. In addition, connecting frontline maintenance teams with inventory levels and location can also reduce the costs of unnecessary parts purchases.

Improving Asset Utilization

Maximizing the utilization of field equipment employed on jobs is critical to the success of OFS companies. Data from digitalizing the frontline can significantly boost ROI by providing an understanding of asset condition and location, driving process efficiency and delivering real-time data for better asset allocation. Analyzing the efficiency of asset turn-around, coupled with performance and inventory data, helps get equipment back into the field more quickly by identifying common process delays and ensuring application-specific training. Having real-time visibility of asset condition and location can enable better allocation of assets among offices and faster response times to customer requests.

Data-driven Pricing Optimization

Understanding the true costs of asset deployment and maintenance provides critical insights for pricing models in OFS. Using data from frontline maintenance and repair activities can deliver visibility into the overall cost of operations and local/regional differences in the costs of repairs. Full visibility into costs enables the development of both more accurate pricing models that account for variations in location and usage, and also more innovative pricing programs or service contracts that provide OFS companies competitive advantages while ensuring profitable operations.

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Closing the Loop on In-Process Defect Repair in MTO Manufacturing

As manufacturing companies continue to adapt to the challenges of the economy, supply chains and the labor market, Make To Order (MTO) concepts have been embraced across industries. A Deloitte survey stated that 38% of manufacturers had implemented some make-to-order manufacturing processes, while 27% planned to do so in the coming five years. Seeking benefits like lower inventory costs and more flexibility, companies are also experiencing new challenges like increasing complexity and longer production times.

One area where these challenges seem to repeatedly exist is in the defect to repair loop within the manufacturing process. On a recent plant visit, we observed the quality team conducting inspections at production gates using paper checklists. Those checklists were collected and data entered each day to produce a work list for the next day. We had just recently seen a similar approach on a faster moving line, where inspectors telephoned production team leaders to describe defects and assign operators to follow the unit to complete the fixes. In this case, the company also employed fixers at the end of the line to cover defects that were not addressed.

Unfortunately, the reliance on paper checklists for in-process quality inspections in MTO manufacturing is all too common, and so is the lag time between defect detection and repair, adding cost and increased possibility of defects in finished product. Even implementing digital checklists is not a panacea for shortening the time to defectless products. While collecting more quality data, faster, and in an automated fashion is a significant boost to identifying quality issues and driving corrective actions, there is still a gap between defect and repair that needs a much more responsive solution and greater automation.

Closing The Loop

Forward thinking manufacturing companies are beginning to look to digital technologies to help drive quality by assisting workers with digital work instructions. These technologies can drive, through access to instruction and repetition, better adherence to standard operating procedures which in turn lessens defects. However, what is beginning to happen with the adoption of digital tools are digital silos of information and automation. Digital tools for production workers and digital tools for quality staff.

What is needed is a closed loop approach from defect detection to repair to verification, that aligns the efforts of quality teams with production teams. Consider the example of the MTO manufacturing plant we visited. Instead of a day lag between defect detection and repair, imagine that both quality teams and production teams had digital tools tuned to their specific jobs that could share in a common process.

Mobile apps for in-process inspections could capture and report defects to production teams, whose digital tools could provide work instructions and the ability to document the repairs with notices to quality team members to close the loop. Defect to repair processes would be automated, reducing time to repair and costs of rework for repairs that are now slipping through the process.

Where Quality Meets Execution

The momentum around digital quality management, eQMS, is growing strongly. Estimates of the US market for eQMS were about $8 billion last year with growth of about 10% per year. Most of these systems have a focus on the management of quality policies, documents and data, but lack a strong connection to the execution of quality processes on the frontline. This is particularly the case for in-process quality inspections and defect detection to repair within MTO manufacturing environments.

ROO.AI saw the emerging gap as we worked with MTO manufacturers, and began to develop a frontline digital automation platform to align the work of quality and production teams. ROO.AI digitalizes in-process quality inspection, allowing quality teams to quickly and consistently execute inspections, and automate the collection of defect information including image and video annotation. Defects are instantly visible within the system for reporting purposes and also to production teams. Alerts can be created, defects can be assigned or claimed, repairs executed and status automatically conveyed to quality teams for verification. For MTO manufacturers a record of every inspection defect and repair can be associated with the product for future reference with warranty and service claims or for quality analysis.

Digitalization of the frontline process for quality inspection and defect repair is the way of the future. When MTO manufacturers are ready to take this step, they should avoid the creation of digital silos and adopt a closed loop platform that drives improved quality, faster defect to repair and shorter build times.

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Challenges of Digital Transformation in Manufacturing

Navigating the challenges of digital transformation in manufacturing is no easy feat, but the potential benefits make tackling these obstacles well worth the effort. 

The manufacturing industry is undergoing what can only be described as a seismic shift. The most tech-savvy manufacturers are transforming everything from core manufacturing processes to supply chain management using advanced digital solutions, such as the Internet of Things (IoT), big data, and cloud computing. 

However, not all companies find it equally easy to embrace digital transformation in industrial manufacturing.

What Is Digital Transformation in Manufacturing?

Digital transformation in manufacturing is the process of adopting and integrating digital solutions into the manufacturing ecosystem. 

At the core of digital transformation in manufacturing is the concept of Industry 4.0, which refers to the fourth industrial revolution. This revolution builds on the foundation of automation and computerization from previous industrial revolutions. It takes manufacturing to new heights by connecting machines, products, and people through digital networks. As a result, Industry 4.0 manufacturers can harness real-time data to:

  • Increase efficiency 
  • Make smarter decisions
  • Reduce costs
  • Improve quality control
  • Quickly adapt to changing market demands
  • Gain a competitive edge in the market

According to Gartner, 80 percent of manufacturing CEOs are increasing digital technology investments to counter current economic pressures, including inflation, scarce talent, and supply constraints. For their investments to yield the desired outcomes, manufacturers must overcome the following challenges of digital transformation in manufacturing.

1. Change Is Difficult

Perhaps the most significant challenge associated with digital transformation in manufacturing is the fact that change is always difficult—especially when it requires the whole manufacturing process to adapt to a new way of thinking. Both frontline workers and middle management may be hesitant to abandon familiar workflows and legacy systems in favor of unfamiliar digital technology.

To overcome this challenge, manufacturers need to prioritize communication and provide all employees whose day-to-day tasks are affected with the necessary support and training. One effective solution is to deliver clear instructions in context and at the point of need using modern next-generation digital assistance tools with support for visual guidance. Such tools help ease the transition for employees, and they can also be used to collect data and analytics on employee performance. 

2. The High Initial Cost of Digital Transformation 

Another major hurdle in the journey toward digital transformation in manufacturing is its high initial cost. Small and medium-sized manufacturers are particularly reluctant to take the plunge because they don’t have the same economies of scale or access to funding as larger manufacturers.

However, it’s crucial to remember that the cost of not investing in digital transformation could be far higher than the initial investment required. In fact, not investing could even jeopardize a manufacturer’s ability to compete in the global market by putting it at a disadvantage compared with more technologically advanced companies. Therefore, manufacturers should consider the high initial cost as a necessary investment in the future success of their businesses.

3. Insufficient Knowledge and Experience 

A considerable challenge of digital transformation in manufacturing is the lack of relevant knowledge and experience required to implement advanced manufacturing technologies safely and securely. Unless addressed, this knowledge gap can lead to the misuse of new digital tools, hindering the overall effectiveness of the digital transformation strategy.

Just like when addressing employees’ reluctance to change, manufacturers should prioritize the education and training of their workforce so that each employee can confidently adopt and adapt to the new digital technologies. Moreover, manufacturers can create digital SOPs (Standard Operating Procedures) and combine them with smart automation tools to ensure that frontline workers are always automatically equipped with clear guidelines. 

4. Human Errors

A 2021 study conducted by Deloitte and the Manufacturing Institute (MI) predicts that 2.1 million manufacturing positions will go unfulfilled by 2030. Consequently, it will be increasingly difficult to find employees with plenty of experience with modern digital manufacturing under their belts. That’s bad news because inexperienced employees are more likely to make mistakes, and human errors in manufacturing can be highly disruptive and costly. Therefore, it’s essential to address these mistakes head-on and minimize their impact.

To tackle human errors, manufacturers should invest in a combination of reskilling, upskilling, and digital training initiatives. Reskilling helps employees transition to new roles, upskilling adds new skills to enhance their existing roles, and digital training equips them with the necessary digital skills to excel in the modern manufacturing landscape.

The implementation of digital work instructions (DWI) and visual guidelines can also be highly effective in reducing human errors. These resources ensure that employees have access to accurate and up-to-date information, which minimizes confusion and missteps. 

Overcome All Challenges of Digital Transformation in Manufacturing 

Digital transformation in industrial manufacturing has the potential to be a source of significant competitive advantage for manufacturing companies, helping them improve product quality, expand their offerings, lower maintenance costs, and much more. 

To reap these benefits, manufacturers need to overcome the above-described challenges, and that’s something ROO.AI, the next-generation digital assistant, can help with. 

With ROO.AI, manufacturers can: 

  • Ease the transition to digital solutions, reducing resistance to change
  • Offer on-the-job training to bridge the knowledge gap
  • Minimize human errors with clear, visual instructions
  • Improve employee performance and productivity through data and analytics

Learn more about ROO.AI and how it can help manufacturing companies unlock the full potential of digital transformation. Don’t let the challenges of digital transformation hold you back. 

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What Is a Quality Inspection in Manufacturing?

A Quality inspection in manufacturing is the crucial process of measuring, examining, and testing various aspects of a product. By meticulously comparing the results of quality inspections with predefined specifications or requirements, manufacturers can detect defects in their processes and in their products before they are packaged and shipped. In essence, a quality inspection is a protective shield that defends both manufacturers and consumers from the potential disappointment of defective goods.

Manufacturing inspections are part of a broader strategy known as quality control in manufacturing, which is designed to establish and uphold high standards of excellence in the production process. Let’s dive deeper into the intriguing world of quality control and explore the different types of quality inspections as well as some of the most important (and often overlooked) reasons why they should be performed. 

The Role of Quality Control in Manufacturing

In the intricate dance of product creation, quality control in manufacturing stands as a pivotal player. This strategy rests on best practices, stringent adherence to standards, and meticulous specifications to deliver flawless products. By employing robust quality control measures, companies can:

  • Reduce costs: Quality control allows manufacturers to cut unnecessary expenses associated with defects and rework. By catching errors early or preventing them entirely, companies can avoid the costs of rectifying mistakes down the line.
  • Curb waste: By maintaining high standards and detecting flaws early, quality control can minimize the number of defective products. This leads to less waste, contributing to more sustainable and cost-effective production processes.
  • Protect reputation: A strict quality control process ensures that only high-quality products reach the market, thereby safeguarding a company’s reputation. It reduces the risk of defective goods tarnishing the brand’s image, and in turn, helps maintain customer trust and satisfaction.

Quality Control Versus Quality Assurance 

Quality Assurance and Quality Control are essential components of any effective manufacturing operation, but they serve distinct roles.

QA is a proactive approach to prevent defects by emphasizing the production process. It’s about systematizing quality through the creation and strict adherence to operational procedures during the production processes. This strategy not only ensures the quality of the final product, but also boosts overall efficiency and productivity.

QC, on the other hand, is a continuous process that enforces and verifies adherence to quality standards throughout the manufacturing cycle. It includes various types of quality inspections, from process inspections to final product checks. These steps are crucial for detecting and correcting any deviations before the product reaches the customer. 

Types of Quality Inspections in Manufacturing

The following types of quality inspections each serve a unique purpose and occur at different stages in the manufacturing process, they all contribute to the same overarching goal: to deliver a product that’s up to par every single time.

  • Pre-production inspections: These inspections are performed before the production line comes into action, focusing on the quality of materials and components used. Such proactive measures help detect potential issues early on, thus ensuring a smooth transition to the production inspection stage.
  • In-process inspections: Occurring during the manufacturing process, these inspections involve quality managers or other qualified personnel assessing everything from individual operations to comprehensive functional systems. Their objective is to guarantee that each element enhances the final product’s quality.
  • First Article Inspection (FAI): This refers to an in-depth and comprehensive manufacturing inspection conducted on the first product produced using intended manufacturing methods. It serves as a validation that these methods and processes can consistently produce items meeting the predefined specifications.
  • Final Random Inspections (FRI): Performed when the product is prepared for market release, this quality control method involves testing all finished products or a random sample of the finished product against the specified quality standards. It aids in identifying and correcting any lingering issues before the product reaches customers.
  • Loading inspections: As a final step before the product commences its journey through the supply chains, this inspection ensures that the right quantities of the product are securely and safely loaded for transportation, mitigating any potential issues upon delivery.

These types of quality inspections are all critical checkpoints on the road to exceptional customer satisfaction, ensuring that every product that leaves the factory floor is a shining example of the manufacturer’s commitment to excellence. 

The Importance of Equipment Inspections in Manufacturing 

Without reliable, well-functioning equipment, maintaining consistent product quality is an uphill battle. This is where equipment inspections come into the equation. They ensure the tools of the trade are in top shape, thus minimizing the risk of flaws or failures in the product output. 

Let’s take a closer look at some of the most essential reasons why manufacturers should inspect their equipment: 

  • Ensuring worker safety: Inspections serve to protect the health of employees. They help identify any potential safety issues with the equipment, reducing the risk of workplace injuries and associated costs such as worker compensation claims.
  • Mitigating legal risks: Regular inspections may be required by law. Failing to perform these inspections can result in penalties, fines, and potential liability. Conducting equipment inspections demonstrates due diligence and compliance with legal safety requirements.
  • Lowering maintenance costs: Regular inspections allow early detection of problems, which are cheaper and easier to fix before they escalate. This prevents improper repair and use of faulty equipment, thereby minimizing maintenance costs in the long run.
  • Facilitating effective management decisions: Inspections provide vital information to management, aiding in cost control, budgeting, and planning. The predictability of equipment downtime allows for better scheduling to minimize productivity loss.
  • Improving equipment procurement: Analyzing inspection records over time can inform better decisions about equipment purchases. By identifying recurring problems, management can make informed choices, favoring equipment with better performance and reliability history.
  • Ensuring calibration accuracy: Manufacturing processes often rely heavily on equipment that must perform to exact specifications. This is especially true for equipment whose sole purpose is to measure products and components in process accurately. Regular inspections ensure that such equipment is accurately calibrated, which is essential for maintaining consistent quality. 

In essence, equipment inspections in manufacturing are not just an obligation but an essential strategy for efficient operations, financial prudence, and optimal product quality. They represent a win-win for manufacturers, workers, and customers alike. 

Paper – The Quality Inspection Killer

The conventional method of carrying out inspections, predominantly on paper, poses numerous challenges. It is prone to human errors, data inconsistencies, delays in reporting, and difficulty in tracking and analyzing trends over time. These obstacles often compel manufacturers to rely heavily on specialized Quality staff to conduct inspections, potentially creating bottlenecks and limiting the full potential of the workforce.

Enter modern digital tools like ROO.AI, which is revolutionizing the quality inspection process at every level—from pre-production to in-process checks, final product verification, and equipment inspections. It eliminates the dependency on paper, thereby addressing the standard issues associated with manual documentation.

ROO.AI’s groundbreaking visual interface and guided work instructions ensure that no inspection point is overlooked. The platform’s ability to automate data collection significantly reduces inspection times, providing instant visibility into defects for quality checks and process audits.

But the transformation doesn’t stop there. ROO.AI also empowers the broader workforce to participate more actively in the quality process. By providing clear instructions and real-time feedback, ROO.AI aids in upskilling workers and enabling more self-verification of their work. This strategy not only improves product quality but also enhances production speed. In turn, it impacts both the top line, by enabling faster delivery to the market, and the bottom line, by reducing waste and rework costs.

Conclusion

Quality inspection keeps every successful manufacturing operation on the right track. This rigorous process spans from the assessment of raw materials to final product checks, and even the equipment used, to assure high product quality and safety, reduce costs, enhance efficiency, and safeguard brand reputation.

In this intricate dance of manufacturing, digital tools like ROO.AI have a pivotal role because they boost inspection efficiency and actively involve the workforce in quality processes. As we enter the era of Industry 4.0, ROO.AI’s role, and the role of quality inspection in manufacturing in general, is guaranteed to only become more significant. 

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