by Gary Mintchell | Dec 19, 2023 | Enterprise IT, Manufacturing IT, Operations Management, Software
Once upon a time surveys were the purview of analyst firms and media. None were mathematically rigorous. Most do show trends and yield ideas for thought.
Digital transformation is top of mind for companies who develop and market software solutions but maybe not so much for customers. This survey is from iBase-t. I knew them as an MES supplier, but now the are the company “that simplifies how complex products are built and maintained.” In other words, MES. That’s OK. My background in that application goes back decades.
This original survey of more than 100 discrete manufacturing executives in the U.S. found that a lack of a clearly defined roadmap is the biggest challenge for manufacturers looking to digitally transform their operations.
None of this surprises me. Many studies have found similar statistics. Upper management in manufacturing organizations “know” these problems. They don’t seem to know how to go about implementing solutions. Or, they don’t want to spend the money!
In brief, their study revealed:
- 60% of manufacturers don’t have a clear understanding of the model-based enterprise
- 67% of manufacturers say that less than half their operations are digital
A full 60% of respondents said they did not have a clear understanding of the model-based enterprise (MBE), which employs CAD systems, Product Lifecycle Management (PLM) systems and Manufacturing Execution Systems (MES) to help manufacturers fully digitize their operations.
Respondents confirmed that although paperless manufacturing and digital transformation are very important priorities, more than two-thirds (67%) of manufacturers reported that less than half of their operations are digital.
The survey found that more than half (54.5%) of respondents lack the interoperability across operations to adopt an MBE strategy. An additional 55% said that their manufacturing systems are not mature enough to support MBE.
Other Key findings:
- According to the survey, 62% of total respondents said that they believe paperless manufacturing is “very important” to their organization.
- The top four goals for manufacturers heading into 2024 are efficiency (66%), on-time delivery (66%), done-right first time (49%) and profitability (47%). An MBE strategy empowers manufacturers to reach all of these goals.
by Gary Mintchell | Dec 15, 2023 | Generative AI
Many people express concern about where the development of artificial intelligence will take human society. This thought piece comes from the Human Factors and Ergonomics Society with some suggested guardrails. Certainly worth thinking about.
Artificial intelligence (AI) is being rapidly developed for a wide variety of applications including:
a) Recommendation systems for consumers;
b) Generative AI systems that create images, audio, video, and text;
c) Systems that take on tasks or portions of tasks in safety-critical systems such as aviation, air traffic control, automated process control, drilling, transportation systems and healthcare; and
d) Natural language systems that support conversations.
Although there are a number of challenges associated with the use of AI, including potential long-term effects on employment, wealth disparity, loss of skills, and the development and testing of robust, trustworthy AI software, a critical and immediate concern is the effect of AI on the people who interact with it.
AI has the potential to augment human capabilities and to improve overall human well-being. However, human-decision making and performance can also be negatively impacted by AI systems, resulting in inappropriate decision biasing, reduced awareness and understanding of situational information, and poor performance. Guardrails are needed to protect people from significant harm from these systems, and to support people’s ability to engage with AI usefully and effectively.
A number of organizations have begun to develop principles for the use of AI and the regulations that should be in place for its use. For example, the European Union has introduced the AI act, establishing initial regulations for the use of AI11. The U. S. Department of Defense has stated that AI should be responsible, equitable, traceable, reliable and governable. The White House Office of Science Technology and Policy (OSTP) has issued an AI Bill of Rights stating that AI should (1) be safe and effective, (2) protect people from algorithmic discrimination, (3) have built in data privacy protections, (4) provide notice that it is an AI and explanations for its actions, and (5) allow for human alternatives, considerations and fallback allowing people to opt out of the AI. These are all sound and appropriate principles that need to be further detailed to allow for meaningful and actionable implementation in different settings.
Human factors researchers are in a unique position to provide scientifically based input on the question of how to avoid negative outcomes from AI systems, while retaining the positive effects that AI can provide. Over the past 40 years, this profession has conducted a substantial body of research exploring the effects of AI and automation on human performance, as well as determining the key characteristics of the technology that lead to both good and bad outcomes. In particular, this extensive research base provides details on supporting human safety and effective decision-making when working with AI systems. The ability of people to know when to trust the outputs of AI systems, their ability to understand its capabilities and deficiencies, and their ability to override AI actions, particularly in safety critical situations, is essential for achieving the goals of safe, effective use, avoiding the negative effects of bias or inaccuracy, and allowing for effective, informed decision-making with respect to interaction with AI systems.
With over 3,000 members, the Human Factors and Ergonomics Society (HFES) is the world’s largest nonprofit association for human factors and ergonomics professionals. HFES members include psychologists, engineers and other professionals who have a common interest in working to develop safe, effective, and practical human use of technology, particularly in challenging settings.
Based on research on human performance in operating with automation and AI, HFES provides the following recommended guardrails for AI, to support the goal of safe and effective use of these systems.
- AI Shall Provide Explicit Labeling
- AI Shall not be Used to Commit or Promote Fraud
- AI Shall Avoid and Expose Bias
- Developers of AI Systems Must be Liable for Their Products
- AI Shall be Explainable
- AI Shall be Transparent
- AI Systems Shall be Tested with Human Users
- AI Shall Provide Safety Alerts
- AI shall be Fail Safe
- Autonomous AI Systems Shall be Validated and Certified
by Gary Mintchell | Dec 14, 2023 | Generative AI, Workforce
As I noted in my last post, the two key words for 2023 are Generative AI and Sustainable. This news concerns the release of more Copilots. These are from SymphonyAI. The company claims that generative and predictive AI are enhancing efficiency by 30%, reducing maintenance costs by 50%, and expediting decision-making by 70%. (I don’t know how they can measure the last one and the first two are huge numbers. But I will buy that there should be measurable improvements.) The three announced Copilots are designed to help frontline workers speed operations and improve efficiency.
The three role-based copilots—Plant Performance Copilot, Digital Manufacturing Copilot, and the Connected Worker Copilot—provide enhanced human-like interaction so workers can get beyond standard data analytics and analysis to understand what happened, why, and more importantly, anticipate future events. Assisted by copilots, plant managers, operators, engineers, and technicians can swiftly identify, diagnose, and overcome operational hurdles with instant initiation of corrective and mitigating actions.
Built on SymphonyAI’s next generation predictive and generative AI Industrial Reasoning and Insights Platform (IRIS), the copilots integrate within SymphonyAI industrial applications. The copilots leverage Microsoft Azure OpenAI alongside an industrial knowledge graph that includes events, sensor data, asset details, product documentation and manuals, and reliability and maintenance reports. All three copilots contextualize, process, and analyze data from various manufacturing sources. Data is presented in natural language to create actionable insights, enhance operations, reduce downtime, and bolster overall productivity.
Plant Performance Copilot enables users, including plant managers, maintenance, and reliability engineers, to quickly uncover and implement recommended actions to enhance plant performance by using natural language in a chat format rather than querying databases, interpreting dashboards, or accessing knowledge repositories. It interacts across all relevant data sources for critical asset processes, delivering targeted user assistance, recommends actions, and forecasts plant performance through contextual, proactive insights and automated workflows. Leveraging natural language, it accelerates root cause analysis from generated anomalies, including quantified KPI impact of underperforming assets and processes, along with recommended remediations.
Digital Manufacturing Copilot streamlines and strengthens manufacturing operations by seamlessly tying workflow, production, and asset data together to unveil invaluable production process optimization and bottleneck prevention insights. Generative AI adds a more intuitive ability to run what-if scenarios for production scheduling, boost throughput, and improve overall equipment effectiveness (OEE) metrics.
Connected Worker Copilot can quickly and comprehensively scan machine manuals, procedures, knowledge bases, and other sources of data to provide instant, contextual recommendations and information to users in natural language, enabling them to instantly identify and resolve problems without having to conduct time-consuming research or consult more experienced colleagues. Integrated with SymphonyAI Connected Worker, the copilot streamlines inspections, reduces rework, and minimizes resource waste for frontline workers. Natural language access to troubleshooting guides, maintenance manuals, and procedure documentation fosters smooth operations with clear insights into workflow metrics and assists new employees with a simple screen tap.
by Gary Mintchell | Dec 14, 2023 | Operations Management, Sustainability
If Generative AI is one word of the year for 2023, Sustainable is the other. This news concerns “Tech For Good” digital solutions from Atos.
Paris, France, and Dubai, UAE – December 6, 2023 – Atos today announces the launch of a new global offering designed to help enterprises reach their CSR goals. With 57% of enterprise IT’s carbon footprint attributable to workplace devices, this service offering represents a major step forward in providing clients with access to new sustainable IT solutions.
Since the 2021 announcement of Atos’ partnership with the BSI Kitemark certified startup Circular Computing at COP26, Atos has expanded its portfolio and set up a comprehensive suite of more than 20 “Tech for Good” services and solutions, encompassing social value and accessibility criteria as well as data analytics and user interfaces.
The first segment in the new offering reshapes device lifecycle management. Most companies replace employee laptops every three to four years, with each new device accountable for emissions of more than 300 kg of CO2e (carbon dioxide equivalent). Atos is now working with a global network of industrial partners to offer clients lower-carbon laptop replacement options, including performance-based refresh and extended use, refurbishing, or remanufacturing.
However, to optimize IT assets it is critical to accurately measure their usage and the carbon footprint of digital behaviors. Atos’ new offering includes a set of dashboards that enable end users and executives to better monitor and improve their workplace carbon footprint.
The “Atos Tech 4 Good Assistant” application offers employees real-time feedback about their personal performance against environmental and social parameters. The assistant can recommend actions such as removing unnecessary programs, turning off the laptop or changing settings on the device. The assistant is available via Microsoft Teams or pop-up notifications, and provides a monthly performance report for each end user.
The final part of the sustainable workplace offering provides consolidated data and recommended actions to IT and CSR leaders. These recommendations allow leaders to not only closely monitor and manage their workplace carbon footprint, but also to improve the impact of the service in terms of social value and accessibility. They are designed to support CSR reporting, which is becoming an increasingly challenging task for organizations across the world.
The Atos Tech 4 Good Assistant solution already monitors more than 100 device models, applications and services, and offers 10+ dashboards to track metrics like device redeployment and improved electricity use. The offering has been co-designed with several Atos clients to ensure it meets the needs of different industries and geographies before expanding to more devices and services as it ramps up in 2024.
Tech Foundations is the Atos Group business line leading in managed services, focusing on hybrid cloud infrastructure, employee experience and technology services, through decarbonized, automated and AI-enabled solutions. Its 52,000 employees advance what matters to the world’s businesses, institutions and communities. It is present in 69 countries, with an annual revenue of € 6 billion.
by Gary Mintchell | Dec 13, 2023 | Asset Performance Management, Operations Management
Most of us are still familiar with the variety of Fluke meters we grew up with. The company made a few acquisitions and developed the Fluke Reliability business unit. They do some cool stuff. Here is the latest news from them in the maintenance and reliability front.
- Fluke Reliability has launched the VibXpert 3 Balancer, a next-generation smart field balancing tool that can diagnose and correct rotational unbalance in the field or on the floor.
- The VibXpert 3 Balancer is equipped with six synchronous channels, making it one of the fastest and most accurate solutions available, and its user-friendly interface makes it accessible to technicians of all skill levels.
- The VibXpert 3 Balancer enhances productivity, increases uptime, and reduces maintenance costs, which is especially important in today’s challenging business environment/skills shortage.
This state-of-the-art device can diagnose and correct rotational unbalance in the field or on the floor, solving a leading cause of failure in rotating assets like fans, pumps, and motor-driven tools.
Unlike the current generation tools on the market, the VibXpert 3 Balancer is equipped with six synchronous channels, so it can record multi-channel vibration measurements simultaneously. This lets users quickly take measurements from multiple angles, compare them to historical data, and identify the root cause of the unbalance directly at the source. As a result, it’s one of the fastest and most accurate solutions available.
Detecting unbalance issues early prevents them from developing into costly, hazardous problems. The result is increased uptime, improved productivity and reduced maintenance costs. The interactive interface functions like a tablet, making it accessible to today’s workforce. Its robust and durable design withstands extreme temperatures, moisture, and dust, making it suitable for fieldwork.
