Analytics Matter Analytics Matter from the Analytics Working Group of MESA International

The large language model (think Chat GPT) made quite a splash at the end of 2023. This class of technologies can be applied to many real-world challenges that face industrial enterprises. But what problems are practical to be solved today by the application of LLM technology? The MESA Analytics Working Group discusses the challenges and opportunities that LLM bring to manufacturing. Join us, its a great discussion filled with possibilities for a promising new technology.

The digital twin may be the ultimate expression of digital transformation. The concept of a Digital Twin has evolved and expanded over the years, but at its core, it generally refers to a virtual representation of a physical asset or process that can accurately represent and simulate its equivalent physical asset or process. Digital twins in manufacturing have been
gaining momentum and are increasingly considered valuable tools. However, whether they are "ready for prime time" depends on the specific industry, use case, and the maturity of the digital twin implementation. The MESA analytics working group has assembled an all-star group with the experience to discuss this from several dimensions. Come have a listen and join the conversation!

Knowing where you are on your digital transformation journey is the key to setting goals and identifying and celebrating the wins. But is it healthy to obsess about this score? And whats behind this single number that is expected to define your level of readiness? And compared to whom? In this episode the analytics working group from MESA International will try to unpack all this and get to the root of the value of a digital maturity assessment.

Why do 87% of data science projects fail?

Non-Availability of Quality Data ....

The data is usually raw and may contain many missing or absurd values. In such cases, it sometimes becomes impossible to make the given dataset into a model-friendly dataset. Thus, if the data quality is not good enough, the data science project will likely fail.

What is the anecdote? ... Data Governance.

But the truth is that data governance is a big challenge for each enterprise. According to a Gartner survey, over 90% of data governance projects fail to perform well.

The MESA Analytics Working Group explores what good data governance could be and how it can reasonably be achieved.

The concept of a "manufacturing metaverse" is still in its early stages; however, its potential impact to uncover real-world business value can be observed and measured today.

The MESA Analytics WG Podcast team debates and cuts back to the core of what we can expect today and what we can speculate for the future of a more immersive, integrated cyber-physical manufacturing world.

Chris Monchinski is joined by John Jackiw, Dennis Brandl, Larry White and Steve Hewitt to discuss.

How will industry jobs be affected by the increasing application and integration of analytics. With all the buzz around new technologies in AI/ML, ChatGPT, etc. this topic is “ever” relevant.

Everyone is speculating and considering what this impact will be (some interesting links below)

⁠https://www.whitehouse.gov/wp-content/uploads/2022/12/TTC-EC-CEA-AI-Report-12052022-1.pdf⁠

⁠https://www.mckinsey.com/featured-insights/future-of-work/ai-automation-and-the-future-of-work-ten-things-to-solve-for⁠

⁠https://www.wsj.com/articles/how-ai-change-workplace-af2162ee?mod=Searchresults_pos4&page=1⁠

⁠https://www2.deloitte.com/us/en/insights/focus/technology-and-the-future-of-work.html⁠

In fact, what does Chat GPT think....

The increasing application and integration of analytics in manufacturing will have a significant impact on manufacturing jobs. Here are some ways in which manufacturing jobs may be affected:


Automation and Robotics: Analytics can be used to optimize production processes, identify bottlenecks, and improve efficiency. This often leads to the implementation of automation and robotics technologies in manufacturing facilities. As a result, certain manual and repetitive tasks previously performed by humans may be automated, reducing the need for labor in those areas.
Upskilling and Reskilling: With the integration of analytics, manufacturing jobs will require a higher level of technical proficiency. Workers will need to
acquire new skills to effectively operate and maintain advanced machinery, analyze data, and interpret insights derived from analytics platforms.
Upskilling and reskilling programs will become essential to ensure the existing workforce remains relevant and adaptable.
Data Analysts and Data Scientists: The integration of analytics in manufacturing will create a demand for professionals skilled in data analysis and data science. Manufacturers will need experts who can collect, analyze, and interpret large volumes of data generated by various systems, such as sensors, Internet of Things (IoT) devices, and production equipment. Data analysts and data scientists will play a crucial role in optimizing processes, predicting maintenance needs, and making data-driven decisions.
Quality Control and Predictive Maintenance: Analytics can improve quality control processes by monitoring production data in real-time, detecting anomalies, and identifying potential defects early in the manufacturing process. This can lead to a reduction in the number of manual inspections required, but it will also create a need for skilled technicians who can oversee and maintain the analytics systems used for quality control and predictive
maintenance.
Decision Support Systems: Analytics can provide valuable insights to support decision-making in manufacturing, such as optimizing inventory levels,
forecasting demand, and identifying cost-saving opportunities. This can lead to more efficient resource allocation and strategic decision-making.
However, decision support systems may also result in a shift in job roles, with a greater emphasis on data-driven decision-making and a reduced need
for manual planning and forecasting.

It is important to note that while some manufacturing jobs may be affected or replaced by automation and analytics, new job opportunities will also emerge as companies adapt to these technologies. Workers with the ability to embrace and leverage analytics, as well as those involved in designing, implementing, and maintaining the analytics systems themselves, will likely find new avenues for employment in the evolving manufacturing landscape.