Factory Floor 2.0: Real-Time Production Tracking

Factory Floor 2.0: Real-Time Production Tracking

Client

Orient Craft

Orient Craft

Year

2023

Summary

Revamping Ridged’s brand identity and digital presence with creative brand identity and captivating digital design solutions.

Diabetes app with predictive glucose insights, personalized dosing, and care-circle support.

Revamping Ridged’s brand identity and digital presence with creative brand identity and captivating digital design solutions.

Overview
Overview

ThreadTrack is a mobile app that captures real-time production data from the sewing line, helping teams log units, flag delays, and stay aligned across departments. Built with Orient Craft, it replaced paper logs and WhatsApp updates with a centralized, tap-to-log system designed for high-volume, fast-paced floors. I led the full design process — from on-site research to prototyping and testing — ensuring it fit seamlessly into daily routines while improving visibility and coordination.

ThreadTrack is a mobile app that captures real-time production data from the sewing line, helping teams log units, flag delays, and stay aligned across departments. Built with Orient Craft, it replaced paper logs and WhatsApp updates with a centralized, tap-to-log system designed for high-volume, fast-paced floors. I led the full design process — from on-site research to prototyping and testing — ensuring it fit seamlessly into daily routines while improving visibility and coordination.

ThreadTrack is a mobile app that captures real-time production data from the sewing line, helping teams log units, flag delays, and stay aligned across departments. Built with Orient Craft, it replaced paper logs and WhatsApp updates with a centralized, tap-to-log system designed for high-volume, fast-paced floors. I led the full design process — from on-site research to prototyping and testing — ensuring it fit seamlessly into daily routines while improving visibility and coordination.

Client

Client

Orient Craft

Orient Craft

Industry

Industry

Manufacturing

Manufacturing

Service

Service

Task Analysis

Task Analysis

Interface Design

Interface Design

Duration

Duration

30 weeks

30 weeks

The Challenge

The Challenge

The first thing I noticed wasn’t the UI—because there wasn’t one. As depicted, production data lived in notebooks and heads. Operators filled out forms hours later—if at all. Managers made decisions based on incomplete or outdated numbers, with no way to track performance by the hour or catch issues in time to act. This was Orient Craft’s largest unit, producing over 12,000 garments a day. But without a system, no one had a reliable, real-time view of what was happening—or what was going wrong.

The first thing I noticed wasn’t the UI—because there wasn’t one. As depicted, production data lived in notebooks and heads. Operators filled out forms hours later—if at all. Managers made decisions based on incomplete or outdated numbers, with no way to track performance by the hour or catch issues in time to act. This was Orient Craft’s largest unit, producing over 12,000 garments a day. But without a system, no one had a reliable, real-time view of what was happening—or what was going wrong.

The first thing I noticed wasn’t the UI—because there wasn’t one. As depicted, production data lived in notebooks and heads. Operators filled out forms hours later—if at all. Managers made decisions based on incomplete or outdated numbers, with no way to track performance by the hour or catch issues in time to act. This was Orient Craft’s largest unit, producing over 12,000 garments a day. But without a system, no one had a reliable, real-time view of what was happening—or what was going wrong.

The Process

To design the right solution, I had to start on the floor — not in a meeting room. I embedded myself across three departments: Sewing Operations, Production Management, and Industrial Engineering. Each had their own way of working, none of it aligned. I wasn’t there to ask what they wanted — I was there to see how they got by without a system at all.

The Process

To design the right solution, I had to start on the floor — not in a meeting room. I embedded myself across three departments: Sewing Operations, Production Management, and Industrial Engineering. Each had their own way of working, none of it aligned. I wasn’t there to ask what they wanted — I was there to see how they got by without a system at all.

The Process

To design the right solution, I had to start on the floor — not in a meeting room. I embedded myself across three departments: Sewing Operations, Production Management, and Industrial Engineering. Each had their own way of working, none of it aligned. I wasn’t there to ask what they wanted — I was there to see how they got by without a system at all.

The Process

To design the right solution, I had to start on the floor — not in a meeting room. I embedded myself across three departments: Sewing Operations, Production Management, and Industrial Engineering. Each had their own way of working, none of it aligned. I wasn’t there to ask what they wanted — I was there to see how they got by without a system at all.

Task Flow Tracing

Traced a production order end-to-end—from Production Planning/Cutting Plan release through in-line sewing line logging, End-of-Shift and Daily Production Report reviews, to Rework Scheduling—capturing timestamps, handoff notes, and deviations to build a detailed delay map.

Task Flow Tracing

Traced a production order end-to-end—from Production Planning/Cutting Plan release through in-line sewing line logging, End-of-Shift and Daily Production Report reviews, to Rework Scheduling—capturing timestamps, handoff notes, and deviations to build a detailed delay map.

Contextual Inquiry
Task Flow Tracing

Traced a production order end-to-end—from Production Planning/Cutting Plan release through in-line sewing line logging, End-of-Shift and Daily Production Report reviews, to Rework Scheduling—capturing timestamps, handoff notes, and deviations to build a detailed delay map.

Shadowed operators, managers, and IE engineers on the shop floor during live shifts, documenting manual logging routines and handoff processes. Gathered time-stamped observations, photos of log entries, and direct quotes to build a detailed record of real-world workflows.

Traced a production order end-to-end—from Production Planning/Cutting Plan release through in-line sewing line logging, End-of-Shift and Daily Production Report reviews, to Rework Scheduling—capturing timestamps, handoff notes, and deviations to build a detailed delay map.

Shadowed operators, managers, and IE engineers on the shop floor during live shifts, documenting manual logging routines and handoff processes. Gathered time-stamped observations, photos of log entries, and direct quotes to build a detailed record of real-world workflows.

Contextual Inquiry

Shadowed operators, managers, and IE engineers on the shop floor during live shifts, documenting manual logging routines and handoff processes. Gathered time-stamped observations, photos of log entries, and direct quotes to build a detailed record of real-world workflows.

Task Flow Tracing

Traced a production order end-to-end—from Production Planning/Cutting Plan release through in-line sewing line logging, End-of-Shift and Daily Production Report reviews, to Rework Scheduling—capturing timestamps, handoff notes, and deviations to build a detailed delay map.

Semi-Structured Interviews

Over tea breaks, I sat down with production-floor teams and supervisors to walk through how they log output, flag scrap, and send urgent alerts—surfacing the informal fixes and friction points in their daily routines.

Over tea breaks, I sat down with production-floor teams and supervisors to walk through how they log output, flag scrap, and send urgent alerts—surfacing the informal fixes and friction points in their daily routines.

Over tea breaks, I sat down with production-floor teams and supervisors to walk through how they log output, flag scrap, and send urgent alerts—surfacing the informal fixes and friction points in their daily routines.

Over tea breaks, I sat down with production-floor teams and supervisors to walk through how they log output, flag scrap, and send urgent alerts—surfacing the informal fixes and friction points in their daily routines.

Value Stream Mapping

After analyzing the timestamped flow and deviation data, I translated every production step into a visual timeline, classifying each as value-add, necessary waste, or non-value-add—clearly pinpointing clusters of delays and handoffs for targeted improvements.

After analyzing the timestamped flow and deviation data, I translated every production step into a visual timeline, classifying each as value-add, necessary waste, or non-value-add—clearly pinpointing clusters of delays and handoffs for targeted improvements.

After analyzing the timestamped flow and deviation data, I translated every production step into a visual timeline, classifying each as value-add, necessary waste, or non-value-add—clearly pinpointing clusters of delays and handoffs for targeted improvements.

After analyzing the timestamped flow and deviation data, I translated every production step into a visual timeline, classifying each as value-add, necessary waste, or non-value-add—clearly pinpointing clusters of delays and handoffs for targeted improvements.

Thematic Analysis

Thematic Analysis

Thematic Analysis

Key Insights

Sewing Opreations

Sewing Opreations

Sewing Opreations

Batched Logging

Batched Logging

Observed: Operators defer line-output entries to breaks or shift-end rather than logging in real time.

Impact: Up to 60% of entries are delayed, letting machine jams and scrap spikes go unnoticed.

Production Management

Fragmented Alerts

Production Management

Production Management

Fragmented Alerts

Observed: Critical deviations get shared via WhatsApp instead of the formal log.

Impact: About 20% of issues never enter the official record, forcing reactive firefighting and hidden rework.

Observed: Critical deviations get shared via WhatsApp instead of the formal log.

Impact: About 20% of issues never enter the official record, forcing reactive firefighting and hidden rework.

Industrial Engineering

Manual Consolidation

Observed: IE engineers spend 1–2 hours each afternoon rekeying paper logs into spreadsheets.

Impact: Analysis always runs on yesterday’s data, making same-day corrective actions impossible

Formative Studies

Formative Studies

1

Disruptive Fit

Traditional bras failed to accommodate symmetry, shifting postures or prostheses-making dressing a daily compromise in comfort and confidence.

2

Cognative Load is real

Dressing became mentally taxing — survivors described planning outfits around pain, visibility, and prosthesis behavior.

3

Lost Identity

Overly clinical or infantilizing designs led to emotional detachment — survivors longed for products that reflected their identity, not their condition.

1

Disruptive Fit

Traditional bras failed to accommodate symmetry, shifting postures or prostheses-making dressing a daily compromise in comfort and confidence.

2

Cognative Load is real

Dressing became mentally taxing — survivors described planning outfits around pain, visibility, and prosthesis behavior.

3

Lost Identity

Overly clinical or infantilizing designs led to emotional detachment — survivors longed for products that reflected their identity, not their condition.

"Missing logs weren’t the culprit—it was the fractured flow of data and delayed alerts that destroyed trust and halted action.”

"Missing logs weren’t the culprit—it was the fractured flow of data and delayed alerts that destroyed trust and halted action.”

Formative Studies

Formative Studies

System Design

Having defined what we’re solving and why, it’s time to show how it comes together under the hood and on screen.

Design

These revelations compelled us to redefine our design vision:

These revelations compelled us to redefine our design vision:

Embedded Real-Time Logging

Integrate data entry directly into each operator’s workflow—eliminating batch updates and blind spots.

Embedded Real-Time Logging

Integrate data entry directly into each operator’s workflow—eliminating batch updates and blind spots.

Role driven Visibility

Surface only the metrics and alerts each user needs—so supervisors, engineers, and line workers all stay aligned without noise.

Role driven Visibility

Surface only the metrics and alerts each user needs—so supervisors, engineers, and line workers all stay aligned without noise.

Unified Data Hub

Automate consolidation behind the scenes to replace manual re-keying, ensure a single source of truth, and eliminate version conflicts.

Unified Data Hub

Automate consolidation behind the scenes to replace manual re-keying, ensure a single source of truth, and eliminate version conflicts.

Zero Learning Curve

Deliver instant, intuitive screens with minimal steps—so teams can adopt the tool on day one without formal training.

Zero Learning Curve

Deliver instant, intuitive screens with minimal steps—so teams can adopt the tool on day one without formal training.

Formative Studies

Formative Studies

Design

Design

Built on ISO 9241-210 • FDA Human Factors Guidance • ISO 13485/14155

Built on ISO 9241-210 • FDA Human Factors Guidance • ISO 13485/14155

Empowering

Built on ISO 9241-210 • FDA Human Factors Guidance • ISO 13485/14155

Empowering

Empower every sewing-station operator with a one-tap, in-line mobile interface that captures production data live and feeds it into unified, role-specific dashboards and alerts—turning fragmented logs into trusted, real-time insights and hourly reports.

Empower every sewing-station operator with a one-tap, in-line mobile interface that captures production data live and feeds it into unified, role-specific dashboards and alerts—turning fragmented logs into trusted, real-time insights and hourly reports.

Use Case Diagram

To align with real user workflows and mental models, we mapped each actor—operators, supervisors, and IE engineers—to the tasks they perform. This diagram outlines core functions like logging data, reviewing dashboards, and handling deviations so we keep interactions intuitive and cognitive load low.

To align with real user workflows and mental models, we mapped each actor—operators, supervisors, and IE engineers—to the tasks they perform. This diagram outlines core functions like logging data, reviewing dashboards, and handling deviations so we keep interactions intuitive and cognitive load low.

Use Case Diagram

To align with real user workflows and mental models, we mapped each actor—operators, supervisors, and IE engineers—to the tasks they perform. This diagram outlines core functions like logging data, reviewing dashboards, and handling deviations so we keep interactions intuitive and cognitive load low.

Activity Diagram

We then charted the entire production workflow—step by step—to expose decision points, handoff friction, and memory burden. This clear view highlights exactly where in-line data capture and structured alerts can smooth tasks, cut errors, and keep everyone on the same page.

We then charted the entire production workflow—step by step—to expose decision points, handoff friction, and memory burden. This clear view highlights exactly where in-line data capture and structured alerts can smooth tasks, cut errors, and keep everyone on the same page.

Activity Diagram

We then charted the entire production workflow—step by step—to expose decision points, handoff friction, and memory burden. This clear view highlights exactly where in-line data capture and structured alerts can smooth tasks, cut errors, and keep everyone on the same page.

System Design

Having defined what we’re solving and why, it’s time to show how it comes together under the hood and on screen.

Use Case Diagram

To align with real user workflows and mental models, we mapped each actor—operators, supervisors, and IE engineers—to the tasks they perform. This diagram outlines core functions like logging data, reviewing dashboards, and handling deviations so we keep interactions intuitive and cognitive load low.

Activity Diagram

We then charted the entire production workflow—step by step—to expose decision points, handoff friction, and memory burden. This clear view highlights exactly where in-line data capture and structured alerts can smooth tasks, cut errors, and keep everyone on the same page.

Login

Settings

Create Style

Attendance

Add Attendance

View Attendance

Line Allocate

Mobile Application

Data Entry

Live Dashboard

Analysis

Analysis

Style Management

Style Management

Add/View Buyer

Add/View Buyer

Add/View Buyer

Add/View Buyer

New Buyer

PPC Department

Production Department

Industrial Engineer

Decision Node

System Design

Having defined what we’re solving and why, it’s time to show how it comes together under the hood and on screen.

System Design

Having defined what we’re solving and why, it’s time to show how it comes together under the hood and on screen.

Live Dashboard Insights

Bringing real-time production data into one view reveals hidden correlations—like understaffed lines causing scrap spikes or peak-shift slowdowns. By juxtaposing daily targets, attendance, efficiency, and quality trends, the dashboard surfaces bottlenecks and empowers operators, supervisors, and engineers to adjust workflows and take corrective action confidently.

Bringing real-time production data into one view reveals hidden correlations—like understaffed lines causing scrap spikes or peak-shift slowdowns. By juxtaposing daily targets, attendance, efficiency, and quality trends, the dashboard surfaces bottlenecks and empowers operators, supervisors, and engineers to adjust workflows and take corrective action confidently.

Production Quantities Input

This one-tap entry screen guides operators through each data capture step with minimal cognitive load. At the top, an Upload Garment Image control lets users snap or select a style photo for instant visual confirmation. Below, four clear selectors—Floor, Plot, Style, and Hour—ensure every log entry is tagged with the right context.

This one-tap entry screen guides operators through each data capture step with minimal cognitive load. At the top, an Upload Garment Image control lets users snap or select a style photo for instant visual confirmation. Below, four clear selectors—Floor, Plot, Style, and Hour—ensure every log entry is tagged with the right context.

Production Quantity Review

This screen closes the feedback loop by showing operators how their logged count compares to targets. A prominent gauge displays this hour’s piece count alongside style ID and timestamp, while panels below reveal hourly target, shift goal, cumulative total, and efficiency. By surfacing all metrics in one view, operators can quickly gauge pace and adjust without manual calculations.


This screen closes the feedback loop by showing operators how their logged count compares to targets. A prominent gauge displays this hour’s piece count alongside style ID and timestamp, while panels below reveal hourly target, shift goal, cumulative total, and efficiency. By surfacing all metrics in one view, operators can quickly gauge pace and adjust without manual calculations.


Line Optimization Simulator

Born from our discovery of bottlenecks in staffing and throughput, this feature lets supervisors and IE engineers test “what-if” scenarios on crew size and line speed without disrupting the floor. By running instant simulations against historical performance, teams can identify the optimal mix of operators and machine pace to hit targets with minimal waste. The result: faster, data-driven staffing decisions, leaner operations, and a measurable drop in downtime and scr

Born from our discovery of bottlenecks in staffing and throughput, this feature lets supervisors and IE engineers test “what-if” scenarios on crew size and line speed without disrupting the floor. By running instant simulations against historical performance, teams can identify the optimal mix of operators and machine pace to hit targets with minimal waste. The result: faster, data-driven staffing decisions, leaner operations, and a measurable drop in downtime and scr

Usability &
Summative Testing

Usability &
Summative Testing

To make sure ThreadTrack thrived in the heat of real production, we invited six seasoned line supervisors and IE engineers to tackle our prototype—logging batches, diagnosing KPIs, running simulations, and sharing reports under real production-floor conditions. Their feedback uncovered hidden friction points—like buried “Advanced Options,” low-contrast callouts, overlooked tooltips, and a clumsy report-sharing flow—that we resolved with a clear toggle and hint, richer color contrast, inline help text, and a one-tap share button.

To make sure ThreadTrack thrived in the heat of real production, we invited six seasoned line supervisors and IE engineers to tackle our prototype—logging batches, diagnosing KPIs, running simulations, and sharing reports under real production-floor conditions. Their feedback uncovered hidden friction points—like buried “Advanced Options,” low-contrast callouts, overlooked tooltips, and a clumsy report-sharing flow—that we resolved with a clear toggle and hint, richer color contrast, inline help text, and a one-tap share button.

To make sure ThreadTrack thrived in the heat of real production, we invited six seasoned line supervisors and IE engineers to tackle our prototype—logging batches, diagnosing KPIs, running simulations, and sharing reports under real production-floor conditions. Their feedback uncovered hidden friction points—like buried “Advanced Options,” low-contrast callouts, overlooked tooltips, and a clumsy report-sharing flow—that we resolved with a clear toggle and hint, richer color contrast, inline help text, and a one-tap share button.

75%

reduction in data-entry errors thanks to inline validation and simplified inputs.

55%

of users reported logging and KPI review felt “dramatically faster”

of users reported logging and KPI review felt “dramatically faster”

of users reported logging and KPI review felt “dramatically faster”

8%

average efficiency uplift after supervisors applied simulator insights.

average efficiency uplift after supervisors applied simulator insights.

average efficiency uplift after supervisors applied simulator insights.

3 of 4

corrective actions were initiated within the same shift of deviation detection.

corrective actions were initiated within the same shift of deviation detection.

corrective actions were initiated within the same shift of deviation detection.

Outcome

Outcome

ThreadTrack eliminated paper logs and WhatsApp alerts, cutting administrative overhead by 30% and restoring real-time data trust. New users reached proficiency in under 10 minutes—50% faster training—and 90% of supervisors adopted the simulator within a week. Automated audit trails captured 100% of deviations and corrective actions, boosting traceability. These changes cemented proactive, data-driven decision-making as the new floor standard.

ThreadTrack eliminated paper logs and WhatsApp alerts, cutting administrative overhead by 30% and restoring real-time data trust. New users reached proficiency in under 10 minutes—50% faster training—and 90% of supervisors adopted the simulator within a week. Automated audit trails captured 100% of deviations and corrective actions, boosting traceability. These changes cemented proactive, data-driven decision-making as the new floor standard.

ThreadTrack eliminated paper logs and WhatsApp alerts, cutting administrative overhead by 30% and restoring real-time data trust. New users reached proficiency in under 10 minutes—50% faster training—and 90% of supervisors adopted the simulator within a week. Automated audit trails captured 100% of deviations and corrective actions, boosting traceability. These changes cemented proactive, data-driven decision-making as the new floor standard.

PORTFOLIO

PORTFOLIO

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