TL;DR

High-performing industrial operations rely on systematic frameworks, not guesswork. During my internship at P&G October 6 Plant, my focus was applying Integrated Work System (IWS) principles, Daily Management Systems (DMS), and targeted loss elimination tools to build a zero-loss culture across physical plant floor operations and digital workflows.

Internship Overview

Standardizing the Foundation (P&G IWS & DMS Alignment)

Before solving individual bottlenecks, the underlying systems needed to be looked into and compared to global KPIs. Using the P&G Integrated work System (IWS) framework, I audited existing daily operations to identify areas for improvement and successful implementation. This included:

DMS Pillar Alignment: Conducted deep-dive audits across the 10 IWS pillars included but not limited to Quality, Autonomous Maintenance (AM), and Progressive Maintenance (PM) pillars.
Global Compliance: Aligned daily routines and KPI mappings with global operational benchmarks, bringing the site to 100% compliance during the P&G IWS Phase Assessment.

Fleet Optimization & Headcount Strategy

Methodology & Loss Elimination Tools

Conducted Motion Time Studies and workflow mapping to construct a Loss Tree for plant-wide machine activity. Built Python (Pandas) scripts to scrape cloud telemetry, feeding clean data into a SQL/Databricks pipeline and a Power BI Equipment Utilization Dashboard without any human intervention.

This was only implemented after a thorough analysis of the existing fleet, which included:

Understanding the operation of the fleet and its role in the plant’s daily operations with daily schedules and shift rotations
Connecting the equipment drivers and shipping conditions to the fleet’s performance

Results

Pinpointed ~47% in uncaptured fleet losses, optimized driver headcount by 21%, and projected ~3M EGP in operational savings.
Developed PowerBI dashboards to visualize fleet performance, enabling real-time decision-making for the utilization of the fleet and its drivers. This included a detailed breakdown of machine downtime, driver efficiency.
Programmed an analysis tool using Python that scrapes equipment telemetry and perform deeper analysis on the operation of the equipment.

Shipping Dock Overhaul Localization

Methodology & Loss Elimination Tools

Applied Root Cause Analysis (RCA) and system breakdown to eliminate persistent dock downtime caused by long lead times on imported OEM parts. Spearheaded physical restoration while sourcing, qualifying, and onboarding new local vendors to reduce lead times.

Results

Restored 5 critical shipping docks (+71% capacity, +21 shipments/day), slashed maintenance costs by 83%, and cut repair lead times by 88%.

Real-Time Budget Forecasting & Financial Control

Applied financial tracking to eliminate budget variance and operational waste to match annual budget with actual expenditures. Forecasted annual operational, maintenance, and repair expenditures while engineering a system that linked projected budgets directly to live, direct expenditure tracking.