Stockpilr is a proactive coal stockpile management app created during a 54-hour hackathon, #UnearthedBrisbane. We solved a problem provided by BMA coal, which roughly costs the industry $120 billion.
I attended my first hackathon few months back and it was a brilliant experience. My team had a good mix of skills with Caleb Hattingh (CEO of Codermoji with entrepreneurship, experience and back-end coding skills), Randall Fenando (Student with back-end and Front-End Coding Skills) and myself (UX designer with UX, UI, Front-End Coding and Presentation Skills). We made a pretty good team and focused on presenting a viable solution in the given 54 hours. (We used only 26 hours though. We were very clear about getting proper sleep and nutrition.)
I have shared the problem we tackled and our proposed solution below with some shots of the interface, branding and the team below.
In theory, different qualities of coal is blended in an efficient manner for purposes such as power generation. However in reality when mining companies want to blend the coal, it is entirely based on guesswork meaning that they are potentially losing billions of dollars every year. The problem stems from the fact that coal is being dumped into stockpiles without any record of how good the quality of the coal is. Currently even the most essential fact like how much coal is in the stockpile is unknown.
Stockpilr is an app to tackle this problem by making it easy for site supervisors to monitor where coal is coming from including important attributes such as the coal quality, how old the coal is, and where it has been sourced from.Currently, a coal stockpile is like a black box: the history of sections of coal within the stockpile is not recorded.
Given mining data, pit and seam, and the geo coordinates of
(A) where mined coal was dumped, and
(B) where coal is collected for downstream,
our application will provide an up-to-date dashboard that provides color-coded information about the grade and age of coal within the stockpile.
Stockpilr will help BMA to make informed decisions based on the monitoring and forecasting features provided.
Directions moving forward
1. Data importer: add data from various sources for visualisation
2. Blend-building recipes: Stockpilr could produce instruction sheets for collecting coal from various locations to meet a blend requirement (cut sheets)
3. Improve degradation models: downstream coal performance could be added to Stockpilr to compare predicted quality against measured quality
4. Track the source: Stockpilr will allow geologists to identify at which pit (and potentially seam) a batch of coal was mined. Downstream problems could be traced to the source.
You can view the site here.
(Very shocking.. But, coded for tablet and laptop screens due to time limitations and the implementation is very shaky.)
I did a quick branding to complement our solution and chose a bold colour palette to work with the UI.
I designed and coded a simple User Interface which will convey the information necessary with minimal fuss while Caleb and Randall took care of server setup, back-end coding, mapping, hooking data to the UI, etc… We decided to design and code only three screens which will showcase the proposed solution to our judges.
Photographs from the day
— Justin Strharsky (@JustinStrharsky) May 17, 2015
We did not win but apparently we were very close or that is what a couple of judges told us. All in all we had so much fun and it was a great experience.