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Production Scheduling Re-Invented

SOUTHWEST Session: LillyWorks’ Protected Flow Manufacturing (PFM) solves “The Late Problem” for manufacturers by implementing the “Dynamic Production Method” (DPM). DPM applies 3 principles from Lean/TOC and other manufacturing improvement techniques to deliver fast results so that Manufacturers can quickly see their On-Time Delivery go up, and their production lead-times go down. Manufacturers can implement DPM quickly using LillyWorks’ Protected Flow Manufacturing (PFM) software. PFM speeds the flow of information to production personnel, so they have the visibility to make the right decisions to accelerate the flow of material and workorders through the manufacturing shop. Manufacturers implementing PFM typically see significant improvements in OTD, reductions in production leadtimes, and increased throughput within 60 – 90 days. PFM can be used in a stand-alone mode, or tied directly to the company’s ERP system.

Digital Threads and Smart Factories: The IoT Advantage in Manufacturing

SOUTHWEST Session: As global manufacturing enters the next wave of industrial transformation, the convergence of digital threads and IoT is reshaping the way products are designed, built, and maintained. A digital thread creates a seamless flow of data across the product lifecycle — from design and engineering to production and aftermarket service. When paired with IoT-enabled smart factories, this integration unlocks unprecedented operational visibility, agility, and intelligence. This session explores how manufacturers are leveraging IoT to create connected ecosystems that power predictive maintenance, real-time quality control, autonomous operations, and closed-loop decision-making. We will discuss practical frameworks for implementing digital threads and highlight ROI-driven success stories from discrete and process manufacturing. Participants will walk away with a clear understanding of: The role of IoT sensors, edge computing, and AI in transforming factory floors Use cases that demonstrate measurable gains in OEE, sustainability, and workforce efficiency A roadmap for integrating IoT into existing manufacturing systems without disrupting operations This talk is essential for manufacturing leaders looking to accelerate their Industry 4.0 journey and future-proof their operations through connected intelligence.  

Matt Jones

Speaker at SOUTHWEST: Matt Jones, Head of GTM, NA, Augmentus Robotics

Nicky Pettit

Speaker at SOUTHWEST: Nicky Pettit, Account Executive, Limble

How Lean Teams Cut Downtime and Boost Output with Smart Maintenance

SOUTHWEST Session: Unexpected breakdowns, rising costs, and limited asset visibility continue to be a challenge for manufacturers, especially as teams face mounting pressure to do more with less – fewer technicians, tighter budgets, and limited time. But with the right technology and a practical approach to reliability, lean teams can shift from fighting fires to building long-term, operational resilience into every layer of production. In this session, we’ll showcase how manufacturers are using modern CMMS (Computerized Maintenance Management System) tools to drive higher uptime, extend asset life, and reduce reactive work – all without needing additional headcount or new equipment. We’ll demonstrate how top performing teams have digitized preventive maintenance schedules, deployed QR code-enabled work orders, and built mobile-first maintenance workflows that keep machines running and teams aligned. Whether you’re still using spreadsheets or looking to get more out of your current system, this session will provide a clear blueprint for building a smart, scalable maintenance program.

Tim Gicewicz

Speaker at SOUTHWEST: Tim Gicewicz, Sr. Solutions Architect, TDK SensEI (USA)

Edge AI: The Future of Industrial Machine Health Monitoring

SOUTHWEST Session: Driven by the rise of Edge AI, industrial machine health monitoring is undergoing a transformative shift—enabling smarter, faster, and more autonomous decision-making at the edge. In this session, we’ll explore how edge computing and artificial intelligence are converging to deliver real-time insights directly at the source of data generation, minimizing latency and enhancing responsiveness. We'll examine traditional Condition-based Monitoring (CbM) methods and their limitations in dynamic industrial environments, then dive into how predictive and prescriptive maintenance strategies—utilizing Edge AI—are anticipating failures, optimizing performance, and reducing costly downtime. This evolution is reshaping the future of industrial reliability, operational efficiency, and long-term asset sustainability.

Real Adoption of Automation & Physical AI in Small & Mid-size Manufacturers

SOUTHWEST Session: Manufacturers from fabricators to assembly shops are all challenged with workforce woes, the need to boost productivity and the endless quest for quality. Knowing automation is the answer is one thing, but actually finding real success with technology investments can feel challenging and risky. How do you know what will truly bring value to the organization? How do you determine the return? And now with the hype of Artificial Intelligence (AI) seemingly on every product, how do manufacturing leaders determine the right places to invest limited time and capital budgets? In this session, we will delve into the ever-evolving landscape of automation & AI in the factory and take a look at technologies that are having a real impact today across the shop floor. Then we will stare into the crystal ball to look forward at technologies that are on the near horizon that manufacturing leaders should be keeping an eye on. Covering important topics like human-robot collaboration, automated equipment tending, data-driven insights, cobot welding, predictive maintenance, robot guided vision, bin picking, collaborative automation, quality inspections, and much more, attendees should leave this session ready to make value-creating technology investments in their business. Join us as we explore how AI is reshaping the factory floor — one algorithm at a time.