Generative Ai For Production Planning Professionals

1000+ Prompts for Daily Decisions in Production Planning

What you'll learn

Identify how AI bridges gaps in conventional production planning methods.

Learn how Generative AI transforms data into production intelligence.

Use over 1000 expert-level prompts to automate every stage of planning.

Apply zero-shot, one-shot, and few-shot prompting for planning tasks.

Design instructional and analytical prompts for accurate production insights.

Create chained prompts to simulate end-to-end planning workflows.

Implement AI-driven trend, moving average, and seasonal forecasting.

Simulate demand surges, variability, and customer-specific scenarios.

Adjust forecasts dynamically based on real-time market conditions.

Track forecast accuracy and initiate automated correction loops.

Understand MPS fundamentals and their central role in planning.

Build weekly and monthly production schedules with AI prompts.

Resolve schedule conflicts and overloads using AI prioritization.

Adjust MPS dynamically using AI feedback from MES and IoT.

Generate AI-driven BOM explosions and procurement recommendations.

Perform shortage analysis and generate replenishment triggers with prompts.

Simulate what-if MRP scenarios and material flow outcomes.

Reschedule MRP operations intelligently based on delay recovery logic.

Understand the difference between finite and infinite capacity models.

Use AI to balance shop load across multiple production centers.

Detect capacity bottlenecks early and plan mitigation strategies.

Automate forward/backward capacity planning using AI tools.

Apply dispatch rules via AI for real-time execution accuracy.

Integrate live status updates from MES and IoT into planning decisions.

Optimize inventory levels with AI-generated safety stock and EOQ values.

Balance stock intelligently across multiple plant and warehouse locations.

Factor warehouse space constraints into scheduling decisions using prompts.

Analyze cycle count deviations and generate adjustment proposals.

Detect risks in production plans using prompt-based risk assessments.

Generate scenarios for machine breakdowns, supplier issues, or demand spikes.

Create AI-driven contingency plans like line activation or load shifting.

Design lean recovery workflows after production disruptions.

Draft executive-level narratives explaining the production plan clearly.

Requirements

A foundational understanding of production and manufacturing workflows.

Description

This course, "Generative AI for Production Planning Professionals," offers an in-depth exploration of how modern AI techniques—particularly generative AI—are revolutionizing production planning. It begins by laying strong foundations through core concepts, planning objectives, and the distinctions between strategic, tactical, and operational planning. Participants will gain insights into the evolution from traditional planning approaches to AI-augmented systems that drive precision and agility. Special emphasis is placed on the role of generative AI, including advanced prompting methods such as zero-shot, one-shot, and few-shot techniques, instructional and analytical prompts, and prompt chaining for sequential logic building.Learners will delve into AI-enhanced forecasting techniques that include trend-based, moving average, seasonal, and dynamic demand adjustments driven by real-time market signals. The course also focuses on ensuring forecast accuracy through monitoring and correction loops. It then transitions into Master Production Scheduling (MPS), showing how AI supports weekly and monthly planning, overload resolution, and real-time adjustments via feedback loops. In material planning, topics include BOM explosion automation, shortage analysis, and AI-driven what-if simulations for rescheduling and delay recovery.Capacity planning is comprehensively addressed, covering finite/infinite modeling, shop load balancing, bottleneck resolution, and dispatch rules. Students will also explore IoT and MES integrations for real-time insights, and inventory optimization through AI-generated safety stock, reorder point, and warehouse balancing prompts. Risk assessment, scenario simulations, and contingency plan generation form a key part of the curriculum, preparing professionals to handle uncertainty with confidence.Finally, the course empowers learners with capabilities in narrative generation, KPI dashboard creation, audit traceability, and planning justification. With over 1000 expert prompts, the course equips participants with practical tools to apply AI across every facet of production planning, making it an essential training for forward-thinking professionals aiming to lead in Industry 4.0 environments.

Overview

Section 1: Introduction

Lecture 1 Introduction - Core Concepts of Production Planning

Lecture 2 Generative AI in Context of Production Planning

Lecture 3 Course Setup - Downloadable files

Section 2: Mastering Prompt Engineering in Production Context

Lecture 4 Zero-shot, one-shot, few-shot prompting using production data

Lecture 5 Instructional and analytical prompting

Lecture 6 Prompt Chaining

Section 3: Demand Forecasting and Sales Planning with AI

Lecture 7 Forecasting Methods Enhanced by AI

Lecture 8 Generative Prompts for Scenario-Based Forecasting

Lecture 9 Dynamic Forecast Adjustments Based on Market Signals

Lecture 10 Forecast Accuracy Monitoring and Correction Loops

Section 4: Master Production Scheduling (MPS) with Generative AI

Lecture 11 Fundamentals of MPS and its Role in Production Planning

Lecture 12 AI-Based Weekly and Monthly Scheduling Models

Lecture 13 Managing Conflicts and Overloads with Generative AI

Lecture 14 Monitoring and Adjusting MPS in Real-Time with AI Feedback

Section 5: Material Requirement Planning (MRP) with AI

Lecture 15 AI-Enhanced BOM Explosion and Procurement Timing

Lecture 16 Shortage Analysis and Replenishment Recommendations

Lecture 17 What-if Simulation for MRP Scenarios

Lecture 18 AI-Driven MRP Rescheduling with Delay Recovery Plans

Section 6: Capacity Planning and Resource Utilization

Lecture 19 Finite vs Infinite Capacity Planning

Lecture 20 Shop Load Balancing with Generative AI

Lecture 21 Capacity Bottleneck Identification and Resolution

Lecture 22 Forward/Backward Capacity Planning Automation

Section 7: Shop Floor Control and Dispatching Prompts

Lecture 23 AI-Driven Dispatch Rules for Real-Time Execution

Lecture 24 Live Status Updates from MES and IoT Integration

Section 8: Inventory Control and Warehouse Sync

Lecture 25 Inventory Optimization Using AI-Generated Insights

Lecture 26 Prompts for Stock Balancing Across Locations

Lecture 27 Warehouse Constraints in Production Planning

Lecture 28 Cycle Count Analysis and Adjustment Proposals

Section 9: Disruption Management and Scenario Planning

Lecture 29 Prompting AI to Identify Planning Risks

Lecture 30 Scenario Generation: Machine Failure, Delay, Demand Spike

Section 10: Narrative Generation

Lecture 31 Narrative Generation: Explaining the Production Plan to Leaders

Section 11: 1000+ Prompts- Generative AI for Production Planning

Lecture 32 Production Planning from Sales Forecasts

Lecture 33 Monthly Capacity Planning and Line Allocation

Lecture 34 Product Mix Optimization

Lecture 35 Bottleneck Resource Allocation

Lecture 36 Make-to-Order vs Make-to-Stock Prompt Logic

Lecture 37 Weekly Scheduling Based on Priority and Capacity

Lecture 38 Changeover Optimization and Setup Time Minimization

Lecture 39 AI-Driven Sequencing for Multi-Product Lines

Lecture 40 Preventive Maintenance Window Planning

Lecture 41 Alternate Routing for Work Orders

Lecture 42 BOM Explosion and Net Requirement Calculation

Lecture 43 Material Availability Checks Before Scheduling

Lecture 44 AI-Based Purchase Requisition Timing

Lecture 45 Substitute Material Planning

Lecture 46 MRP Exception Handling (Shortages, Delays)

Lecture 47 Sales Trend-Based Forecasting

Lecture 48 Moving Average and Weighted Forecasts

Lecture 49 Forecast Recalibration Based on Real Demand

Lecture 50 Seasonal and Cyclic Demand Forecasting

Lecture 51 Simulation of Demand Spike or Drop

Lecture 52 Inventory Level Monitoring Prompts

Lecture 53 Safety Stock Recalculation

Lecture 54 Reorder Point and EOQ Analysis

Lecture 55 Inter-plant Transfer Suggestions

Lecture 56 Warehouse Space Constraints in Scheduling

Lecture 57 Finite vs Infinite Capacity Models

Lecture 58 Load Balancing Between Work Centers

Lecture 59 Labor and Machine Shift Matching

Lecture 60 Real-Time Capacity Overload Handling

Lecture 61 Dynamic Shop Floor Workload Analysis

Lecture 62 Daily Production Summary Report Generation

Lecture 63 OTIF and Schedule Adherence Dashboards

Lecture 64 Scrap and Rework Trend Analysis

Lecture 65 Machine Utilization KPIs via Prompting

Lecture 66 Production Variance Explanation Generator

Lecture 67 AI Alerts for Missed Deliveries or WOs

Lecture 68 Risk-Based Prioritization of Work Orders

Lecture 69 Disruption Simulation (machine, supplier, demand)

Lecture 70 Emergency Replanning After Failures

Lecture 71 Lean Recovery Planning from Downtime

Lecture 72 Production Plan Narratives for Executives

Lecture 73 Planning Justification Memos (why X was prioritized)

Lecture 74 Handoff Reports to Maintenance and QA Teams

Lecture 75 Real-Time Shop Floor Bulletins

Lecture 76 Email or Chat Summary Generators for Shift Changes

Lecture 77 Historical Data Pattern Analysis via Prompts

Lecture 78 Continuous Improvement Suggestions from AI

Lecture 79 Model Retraining via Feedback Loops

Lecture 80 KPI-Based Recalibration Prompts

Lecture 81 Planning Audit Trail and Traceability Prompts

Production Planners looking to automate scheduling, MRP, and capacity tasks using AI prompts,Operations Managers aiming to integrate AI into real-time shop floor decision-making,Manufacturing Engineers seeking to simulate production scenarios and optimize workflows,Supply Chain Analysts who want to align planning with inventory and procurement using AI,Demand Planners needing AI-driven forecasting, seasonal analysis, and signal-based adjustments,Industrial Engineers interested in prompt-based workload distribution and load balancing,ERP Specialists and MES users wishing to extend existing systems with AI augmentation,Quality Managers and Maintenance Heads who rely on synchronized planning inputs,Professionals transitioning into Smart Manufacturing and Industry 4.0 roles,Executives and Digital Transformation Leaders overseeing AI implementation in planning