E-spine
LHP and Ring-Co Transit - Design Challenge for Business Optimization
Real-time yard equipment performance analysis to anticipate failure before it happens and take proactive measures to reduce the risk of failure.
Intermodal Shipping yard equipment management
Industry
8 weeks
Project duration
User research / Concept ideation / Market strategy /Wireframes /
Skills
Product design lead
My Role



Company objective
Project brief
Untowed JV, a new to be launched venture between Ring co transit and LHP Analytics , is interested in establishing itself as the leader in Yard Management Systems.
Untowed JV aims to address the bottleneck in the supply chain caused by poor communication and lack of visibility in the yard.
The solution should improve the flow of goods from road to dock, increase operational efficiency, and ensure timely deliveries.

Ring co transit brings Autonomous Vehicle


LHP brings its analytics software power
Solution Overview
Non functioning equipment in the yard have consequences resulting in high cost of functioning.
Problem explored
One platform to easily monitor performance and maintenance of the equipment throughout its life cycle with cost effectiveness.
Solution presented
Making it easier for facility managers and maintenance team to work collaboratively to reduce equipment downtime
Target Users
Computerized maintenance management software (CMMS) dashboard that offers
1
2
3
Equipment downtime tracking and analysis
Automatic anomaly detection in machines
Error Pattern recognition for proactive maintenance
4
5
6
Customizable dashboard with quick information KPIs
Yard Efficiency reports and analysis
Maintenance expenditure trends and Cost saving analysis
Solution Impact
based on optimization results offered by similar solutions in the market
90%
Reduction in technician time spent filling work orders and locating asset information
70%
Decrease in breakdowns over the life span of the asset.
20%
Increase in the lifetime of an asset due to decreased risk of failure and proactive safety measures
My Contribution
primary research + product ideation + business model canvas + wire-frames
Results
The IOT ecosystem needs to be worked upon in detail such as sensor types and gateways to make solution truly feasible.
Feedback
Getting familiar with the industry with environmental analysis and narrowing down one practical solution.
Learning
Jumped too early into prototype design without through research on the KPIs and the associated data visualization
Takeaway
Conceptual wireframes
Future Roadmap
Collaborating with data scientists and machine engineers to determine the right set of KPIs needed.
Contextual User research on the work flow of facility managers to design the dashboad's collaborative features,
Design Process

Product Ideation and Business Strategy
Research Questions
What is Intermodal hub and how does it function.
Automation in Yards and Industry 4.0 solutions.
Current key players and market trends.
Factors affecting the market.
Choke points in the yard, warehouse and transportation systems.
Secondary Research
Environmental Analysis of the industry from macro to micro economic forces.
YouTube videos, tutorials and Intermodal hub journals.
Primary Research
Interviews with industry experts from Intermodal Association of North America.
Research Outcomes
Key insights from empathy mapping, environmental analysis, user personas and customer profiles
Problems with lights, tires, and other mechanical features on many chassis available for lease today
Visibility issues : Hazardous weather conditions make it impossible for labour to work and causes visibility issues in the yard for crane operators.
Trucks and Rail backlogs due to longer equipment downtime
Fuel costs rising : Additional cost and pollution dangers loom due to increased fuel consumption by equipment
Intermodal shippers often complain of a chassis shortage, but plenty of chassis are available.They’re simply piling up in inconvenient locations.
Inefficient Maintenance : A Big Contributor To Unplanned Downtime
We presented three problem statements, one for each persona user to demonstrate their pains and needs. For each problem, we presented one solution to the clients through sketches and storyboards after crazy 8 exercise.
Out of three ideas, we prioritized one solution based on market insights and SWOT ANALYSIS
Problem Statements
Solution- real time awareness
01

As a Strategy Officer
When I want to deliver the time sensitive cargo
I want to have real-time awareness about it's status
So I can schedule the trucks accordingly
But I don't know where the cargo is stuck.
Strenth
Weakness
Opportunities
Threats
02
As a Maintenance Officer
When I go on holidays
I want to make sure all equipment are in good standing status
So I can utilize my break time freely
But equipment downtime is very unexpected
Solution- Organization through proactive maintenance
Fixed sensors
RTGS
CRANES
CHASSIS
Information processing and Data Analysis using machine learning algorithms
Live scans like thermal and noise anomaly detection through moving sensors on AV
Maintenance schedule generated by AI accesible through dahsboard
Strenth
Weakness
Opportunities
Threats
03
As a Crane operator
When I am stacking trailers on the trucks
I want to align it correctly
So It doesn't become a safety hazard while its on road
But visibility issues keep arising due to various factors
Solution- Mixed reality incorporation for visibility

Strenth
Weakness
Opportunities
Threats
Prioritization of solution

Final Pick
Solution 2- Maintenance management
75%
Terminals will turn to industry
4.0 solution by 2030
$5.95 bn
The global predictive maintenance market
Marketing Channels

Cost Structure

Revenue Streams

Metrics to measure - Value proposition
(1)Tem: Total time for emergency maintenance
(2) Tps: Total time for preventive maintenance
(3) Fem: Frequency of emergency breakdown
(4) TLC: Twist lock count (lock + hoisting‑lowering + unlock)
(5) Top: Total operating time of crane (gantry + boom hoist + main hoist + trolley‑overlappingmotion of main hoist & trolley)
(6) Tno: Time of net operation (main hoist + trolley‑overlapping main hoist/trolley)
(7) Toc: Total occupied time (control source on time)
(8) Tmc: Total machine time (24 h/day for 24 hour terminal operations)
(9) MMBF: Mean movements between failure (calculation formula: TLC/Fem)
(10) MTTR: Mean time to repair (calculation formula: Tem/Fem)
(11) Utilization: operation time (calculation formula: (Top/ (Tmc - Tps - Tem)) × 100%)
(12) Ai: Overall availability (calculation formula: ((Tmc - Tem - Tps)/Tmc) × 100%)
(13) Ao: Availability per occupied time (calculation formula: ((Toc - Tem)/Toc) × 100%)
(14) Breakdown percentage (calculation formula: 1 - Ao%)
(15) PM: Preventive maintenance (calculation formula: (Tps/Tmc) × 100%)
(16) EM: Emergency maintenance (calculation formula: (Tem/Tmc) × 100%)
(17) TDT: Total downtime (calculation formula: 1 - Ai or (PM% + EM%))
(18) Net cycle time: pure time to handle 1 VAN of a container (calculation formula: (Tno ×60)/TLC)(19)
Challenges resolved
Pay more for maintenance.
Suffer low technician productivity
No spare parts when needed
Unavailable outside contractors at the time of need.
70% of unplanned downtime results from human error.
$35,000 loss a day, for every crane that’s not in operation.

Current series of events

Replaced by new ecosystem
Design Challenges and Constraints
Solution

The product ideation process also included lot of behind the desk work through various UX design methods, market research and multiple iterations of wire-frames
I would love to connect further to talk about the project in detail.
Thankyou for reading!