Tag: Chat GPT

OM in the News: AI Is Becoming Every Product Designer’s Companion

Artificial intelligence tools like ChatGPT and Microsoft Copilot have already proven their value in many product designers’ daily design work, asking questions about design decisions and giving advice on design and CAD strategies. (See Chapter 5 in your Heizer/Render/Munson OM text). But AI is moving beyond being a tool to becoming an active collaborator, reports Industry Week (Jan. 24, 2025). There are a huge number of exciting AI applications in design:

Generative design as a standard: AI-driven generative design tools are becoming more popular, producing optimized solutions that human designers might never consider. These tools will seamlessly handle constraints like material properties, manufacturability and sustainability.

AI-Powered decision support: Product designers are increasingly relying on AI to analyze massive datasets, predict performance outcomes and recommend design improvements. AI-powered digital engineering tools that accelerate physics simulation through “simulation surrogates” are helping designers make faster, smarter decisions throughout the product lifecycle. AI models trained on numerical analysis can run simulations up to 1,000 times faster.

Human-AI collaboration: The best results come from teams that embrace a symbiotic relationship between AI and human creativity. AI can help human designers answer questions by doing the legwork and analysis on documents and information.  AI will provide expert advice on how to use other computing tools like computer-aided design (CAD), product data management (PDM), and simulation, much like expert human designers provide advice to their colleagues. The latest conceptual industrial design tools take simple sketches and generate rendered design concepts based on text prompts, such as “orange and black controller, Nintendo-like.” Meanwhile, AI assistants for computer-aided manufacturing (CAM) software–see Chapter 7– can quickly produce machining strategies, reducing time spent on CAM programming and making manufacturing processes more efficient.

Customer-centric design: AI is also playing a significant role in aligning products with customer preferences. The latest AI product development solutions mine product reviews and other customer feedback data to synthesize design directions tailored to consumer tastes or specific attributes like performance. This insight can help teams create products that better meet market demands.

Classroom discussion questions:

  1. How is AI revolutionizing product design?
  2. Are there disadvantages in becoming AI-dependent?

Guest Post: How to Leverage AI in your OM Teaching

Dr. Jonathan Jackson is Associate Professor of SCM at Providence College.

Preparing for an upcoming semester is a challenging task for educators in normal circumstances, but infinitely harder when facing the largest disruption in education since the internet. The introduction of generative artificial intelligence (AI) and large language models (LLMs) like ChatGPT have caused us to rethink an entire course.

While AI will inevitably cause challenges, it also provides great opportunity to improve higher education. Here are 4 opportunities to make your teaching easier and more impactful using AI:

1. We have all been in the situation where no matter how we try to explain a challenging topic (e.g., the bullwhip effect), it still isn’t “clicking” for our students. This is where AI can help. By prompting an LLM like ChatGPT with a topic (say, bullwhip) and an audience  (business students), it can help generate alternative explanations at varying levels of complexity to help improve student understanding.

2. Relevant and interesting examples help keep students engaged, but coming up with good examples is no easy task. Similar to generating alternative explanations, AI can provide various examples to help students connect a topic (e.g., inventory management) to things they see in their day-to-day lives.

3. While your Heizer/Render/Munson OM text has an amazing set of questions that can be auto-graded through MyLab, sometimes we need additional questions for a particular topic or class session. For example, before introducing SPC in Supplement 6, we may want to devise a low-stakes quiz to refresh students on topics from their previous statistics course such as central limit theorem and Normal distribution. AI can not only develop the questions, but also provide an answer key and explanations.

4.  Short feedback mechanisms like “1-minute paper” and “muddiest point” are excellent tools to help gauge student understanding and gaps in knowledge. Unfortunately, they can be cumbersome for us to administer on the back end. Specifically, AI can help in summarizing the responses from the 25+ students into important points (understanding) and areas of confusion. By inputting all student responses into the LLM, it can provide  prevalent key points and areas of confusion in a matter of seconds.

Much of the discussion around AI and education comes in an adversarial tone, but these opportunities are framed around leveraging this new technology for the betterment of our courses (and to save us a little time!).

Note: Generative AI and LLMs are not foolproof and should be carefully vetted using your content expertise.