I'm an ex-electrical engineer, now working as a project management and planning consultant, and building my knowledge and experience in software application development, distributed systems, individual and team coordination, predictive models, process efficiency, and other buzz words in that general area. (cough AI, ML cough)
I have some big ideas for helping manufacturing clients manage the quality and efficiency of operations, as well as continuous-processing clients manage their maintenance requirements within their tight timescales preparing for process/plant shutdowns and turnarounds.
We see a lot of clients struggling to implement new technologies when trying to plan and keep track of their complex projects, full of intricate relationships that can have serious impacts on the reliability of their plants, the efficiency of their workforce, and ultimately their bottom line.
The level of sophistication is typically around a lot of manual/semi-automated scheduling and planning of activities, resources, time, and costs; with relatively siloes teams and departments; and where Excel or isolated software packages reigns supreme (ERP, HR, QMS, etc.)
I'm interested in bringing a focused approach to a number of pain points in our client's processes by creating a range of interconnected web-based products.
After some failed attempts at modelling and developing solutions using relational concepts, against limited time and resources, I'm learning how graph theories and DBs can help us to reach our goals quicker.
My particular technical interest is first leveraging distributed Erlang/Elixir systems for fault tolerance and concurrency, along with lean and inobtrusive web-based user interfaces, to enable efficient planning, communication and data-sharing. Then using more advanced topics that seem to naturally follow from a well-designed graph-based system into predictive models and eventually to cloud-based manufacturing.
I am excited to learn, so any and all information that you feel can help me in this, especially in the form of books, papers, and articles, would be greatly appreciated and returned in kind however I am able to.
Thanks for reading this far!
