Projects

Solving what others couldn't

Each of these started as a number somebody could not explain. The work below is described the way it happened — the situation, the diagnosis, what actually changed on the floor, and the result against the original baseline.

+28%
Product quality gain on a vegan cheese line
$2.8M
Cost saved over two years from that one programme
+43%
Overall equipment effectiveness from real-time monitoring
−31%
Production lead time on an upstream drilling programme
01

Vegan food manufacturing

Vancouver, Canada
Industrial cooking vessel on a vegan cheese production line

Situation

A vegan cheese slice line was yielding a product quality rate of 68%. Nearly a third of everything the line produced was being downgraded or scrapped, and the defect pattern was inconsistent enough that no one could point to a single cause.

Diagnosis

A comprehensive root cause analysis across the defect modes pointed at the cooking stage: the process was being run across two separate steps, with atmosphere and thermal conditions varying between them and between shifts. The variation the plant was measuring in the product was variation in the process itself.

What changed

I integrated the two critical production steps into one controlled operation and brought the cook under precise parameter control in a zero-atmosphere condition. That meant mechanical engineering modifications to existing equipment as well as newly designed equipment installed to hold the required operating conditions. Alongside the hardware, I standardised the cooking procedures, rewrote the work instructions and ran extensive training with the operations team.

Result

Product quality rose 28%, generating $2.8 million in cost savings over two years. The consumer experience improved with it, and the strengthened quality record opened the door to partnerships with larger retail and quick-service restaurant customers — a commercial gain the plant had not been able to pursue at 68%.

+28%product quality
$2.8Msaved over two years
68% →starting quality rate
02

Real-time data analytics

Vancouver, Canada
Real-time production dashboards on a laptop and phone

Situation

High-speed manufacturing and packaging lines were being managed on end-of-shift reporting. Losses were visible only after they had happened, and the supply chain team was planning against job order progress it could not see in real time.

Diagnosis

The signals needed to run these lines properly already existed inside the machines. They were simply not being collected, consolidated or put in front of anyone who could act on them within the shift.

What changed

I implemented a real-time performance monitoring system across the lines: laser photo-eye sensors installed at the critical points, signals integrated from the machine PLCs, and the collected data consolidated into a data warehouse. A SaaS platform delivered it back as an interactive dashboard on personal devices and iPads, surfacing performance metrics and the KPIs that actually govern operational efficiency.

Result

Overall Equipment Effectiveness rose 43%, with a corresponding reduction in operating expense. The supply chain team — demand planning in particular — gained the ability to track job order progress accurately and adjust plans while there was still time for the adjustment to matter.

+43%overall equipment effectiveness
LiveKPIs at the machine, on any device
↓ OpExlower operating expense
03

Upstream oil & gas

Texas, USA
Offshore drilling platform

Situation

An upstream drilling programme was running long against plan, with the overrun spread thinly across every phase rather than concentrated in one obvious failure. Day rates made every hour of it expensive.

Diagnosis

I ran an in-depth step-time analysis across each phase of the drilling process, looking specifically for the seven Lean wastes — instances of waiting, excessive motion, over-processing and unnecessary transportation. A 5-Why analysis on each significant loss traced the time back to its root cause rather than its location.

What changed

Working from those findings I developed a streamlined operational plan and re-staged equipment so that what crews needed was where they needed it. The result was the removal of non-value-added activity — the motion and transport time that had been absorbed into the schedule as though it were work.

Result

Overall production lead time fell 31%, with the improvement holding across subsequent phases because the staging plan and the revised sequence were documented rather than remembered.

−31%production lead time
7 wastessystematically eliminated
5-Whyroot cause on every loss

Find out what your operation is losing — and what it would take to stop it

A 30-minute call, no charge and no pitch deck. Tell me what is not working and I will tell you straight whether it is something I can help with.