Baseline Assumptions
​​​​​​Here are the basic assumptions of this discussion:

1. AI is not evil. No Terminator scenarios are considered here.
2. AI will be much smarter than humans. Say 1000x, although there are estimates that are much much higher.
3. Companies are driven primarily by the profit motive. "If we don't use AI, our competitors will and put us out of business."

AI Without Physical Agency

"Physical agency implies that an entity has the capability to interact with its surroundings, manipulate objects, and exert force or energy to achieve specific goals or outcomes." - ChatGPT.

In this level of maturity AI is wicked smart but cannot easily act in the physical world. What kinds of tasks might this level of AI be able to help us with on typical Lean projects? Here are some things that Lean/Manufacturing Engineering folks currently do:

1. Time Studies
2. Standard Work Definition
3. FMEA Analysis
4. Value Stream Design
5. Line Balancing and Visual Work Instructions
6. Visual Inspection
​​​​​​​7. Create Training Materials
8. Conduct live training courses
9. Develop optimum sequencing rules.
10. Line Rebalancing, including new work instructions and training.
11. Rapid response to andon signals.
12. Supply chain and procurement management.
​​​​​​​13. Precise optimization of material delivery systems.

AI With Physical Agency

In this thought experiment we are taking it to the next level, where AI has the ability to manipulate physical objects. Of course this is already happening, on factory floors and warehouses. Here we want to extend the capabilities further, to include robots with more mobility, dexterity and visual acuity, and that are also powered by a 1000x intelligent AI. Here are some of the potential tasks that could then be taken over:

1. Assembly line work.
2. Material warehouse work.
3. Material delivery on the factory floor.
4. Driving delivery trucks and management of external milk-runs.
5. Coordination with supplier AIs to manage the entire supply chain.
6. Integrate (and eliminate) the need for line design, work instructions,  line balancing, training and inspection through real-time analysis and response.

How Soon Might This Happen?

The singularity event, in the context of AI, refers to a hypothetical point in the future when artificial intelligence surpasses human intelligence in virtually all areas, leading to a significant and potentially transformative impact on society and civilization. - ChatGPT

​​​​​​​AI experts, presumably the people who should have a good feel for this, have been expressing alarm at the speed at which AI development is happening. Predictions of when the "singularity" event will occur range from the 2040's to very soon. 

We will conclude the webinar with a "next steps" discussion. What (if anything) can be done to prepare? How can humans and AI work together? If we don't start using AI, at least in the short term, will we be left behind?

The Consequences of Skipping the Modeling Design Step​​​​​​​

Choosing to skip the simulation modeling design step can have far-reaching consequences that undermine your operational efficiency and competitive advantage. Without the insights gained from simulation, you risk making uninformed decisions that lead to suboptimal process designs. By attending our webinar, you will understand the potential pitfalls of neglecting simulation modeling and the missed opportunities for improving productivity, reducing costs, and achieving higher levels of quality. 

The Evolution from Manual to Automated: Revolutionizing Lean Manufacturing

In the past, lean manufacturing specialists relied heavily on manual methods to analyze and optimize processes. They painstakingly collected data, conducted time-consuming calculations, and performed intricate analyses to identify areas of improvement. However, in today's hyper-competitive environments, where speed and agility are paramount, this approach is no longer sufficient.

The paradigm shift towards automation has transformed the way lean manufacturing specialists operate.

​​​​​​​With the advent of advanced technology and powerful AI tools, the landscape of process optimization has been revolutionized. Today, lean practitioners can leverage cutting-edge simulation modeling tools to automate and streamline their analysis processes. By embracing these technological advancements, they can gain a competitive edge by rapidly identifying inefficiencies, implementing changes, and continuously improving their manufacturing operations.

The Role of AI Tools in the Modeling Revolution

One of the key contributors to this revolution is the explosion of AI tools, such as ChatGPT, that have emerged in recent years. These AI-powered tools have significantly simplified and accelerated the development of simulation models. With their natural language processing capabilities, they enable lean manufacturing specialists to interact with the modeling software in a more intuitive and efficient manner.

AI tools like ChatGPT facilitate seamless communication and collaboration between humans and machines. They can understand complex instructions, interpret user queries, and provide real-time responses, thereby reducing the learning curve associated with traditional modeling software. As a result, lean specialists can rapidly prototype and iterate models, evaluate different scenarios, and extract valuable insights at a much faster pace.

​​​​​​​Furthermore, AI tools can assist in automating repetitive tasks, such as data preprocessing and model calibration, freeing up valuable time for lean specialists to focus on higher-level analysis and decision-making. By harnessing the power of AI, lean manufacturing specialists can leverage their domain expertise while benefiting from the efficiency and speed that technology brings to the table.