Controlled copyLast updated 27 Oct 2026MVKR
Available from 12 January 2027

People
Processes
Productivity

KrishnaMadupalli

Mechanical engineer

Manufacturing | Lean | Cutting tools
Production planning | Continuous improvement

Focus
Analyse
Improve
Repeat

Engineering-drawing style portrait of Krishna Madupalli
Ideas
Processes
Better outcomes

Engineering
a more efficient
tomorrow

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All dimensions are in mm

NameKrishna Madupalli
BackgroundManufacturing · MSc, finishing Jan 2027
LocationLondon, UK
StatusOpen to opportunities
Rev00Date27 Oct 2026

Continuous improvement in everything

3D view · Tool · End millExample · Ø12 · 4 flutesRot 000°Drag to rotate

The tools I specify, and the parts they make.

Tools
Parts

01About

Hello, I am Krishna.

I learned manufacturing the practical way: about three years on the production floor (CNC turning, shift planning, audits and improvement projects), then engineering support, then a year helping customers choose cutting tools. Along the way I saw that most quality problems start in the process, not at final inspection. That is why I like Lean and root-cause work, and why my MSc dissertation asks whether machine data can stop scrap before it happens.

I am finishing my MSc at the University of East London, and I am looking for a role where I can keep that practical view and take on more responsibility.

Based in
London, UK
Studying
MSc Mechanical Engineering, University of East London
Open to roles
Mainly production and process improvement in manufacturing: Lean, quality and planning.
Also a strong fit for cutting-tools application engineering and project coordination.

How I work

I am always asking where a process is losing time, material or money, and how to take that loss out. I like to improve the numbers, then keep asking what else could be better.

  1. Measure it. Numbers first: cycle time, rejects, output per shift. If I can measure it, I can show it improved.
  2. Find the cause. I trace a loss back with Pareto, Fishbone and 5 Whys, instead of treating the symptom.
  3. Fix it and hold it. I write the fix into a standard, a routine or an SOP, so the gain is still there next month.
  4. Look ahead. I ask what could go wrong next, the way FMEA does, and deal with it early.

Where I have gone after waste

02Work

What I have worked on

From the shop floor to cutting-tool applications. Pick a stretch of work on the scale, then open the projects below.

Timeline

201920202021202220232024202520262027

2019–21

Kusalava International Ltd

Assistant Engineer · May 2019 to Nov 2021

Where I learned the floor: 95% output or better for 2.5 years, plus three improvement projects.

I started on CNC turning (Jyoti and ACE machines, Fanuc and Siemens controls), then moved into shift planning and production coordination. I investigated rejects above the 2.75% threshold with Pareto, Fishbone and 5 Whys, co-wrote APQP and FMEA documents, supported IATF 16949, ISO 9001 and ISO 14001 audits, and ran the 5S, TPM and VSM projects below.

Projects

01

Clearing the floor

1S and 2S standardisation · Kusalava (ACMA Group) · 2020 to 2021

15+ metres of floor space reclaimed.

Open
1S Sort2S Set in Order

Floor space reclaimed · metres

01020
What happened
I led a plant-wide rollout of Sort and Set in Order, the first two steps of 5S, across 10+ production, quality and stores areas. I defined standard maintenance routines to keep it in place.
How it ended
15+ metres of usable floor space came back, and a monthly scrap-clearing schedule was adopted across the plant.
02

A machine that kept stopping

Equipment Step 123 (TPM) · Kusalava (ACMA Group) · 2021

Breakdowns stopped; 90% audit score.

Open
CleanLubricateInspectTighten

Equipment faults cleared

03060

Equipment audit score · %

050100
What happened
A critical honing machine kept breaking down. I worked through 53 equipment abnormalities using the CLIT method (clean, lubricate, inspect, tighten) and removed hazards such as oil leaks, loose wiring and blocked access.
How it ended
The recurring breakdowns were eliminated and the machine scored 90% in the audit.
03

Finding the bottleneck

Value stream mapping · Kusalava (ACMA Group) · 2021

Output up 36%; cycle time down about 40%.

Open

Output per shift · units

100130160

Cycle time · before = 100

050100

About 40% shorter.

What happened
I mapped a multi-stage production line against the seven wastes, recording the full process flow with the maintenance, CNC programming and operations teams.
How it ended
Output rose from 110 to 150 units a shift and cycle time fell by about 40%.
04

Planning freezer space

Velocity Composites plc, Burnley · Jul to Sep 2026 · University placement

A forecasting model, checked against real data.

Open
Customer demandSupplier lead timesProduction consumptionFreezer capacityforecast
What happened
I built a model that links customer demand, supplier lead times and production use to forecast freezer capacity for aerospace composite raw materials, and checked it against real monitoring data with the Logistics team. A site visit showed that the storage location we had assumed was not the one actually in use, so I corrected the project scope.
How it ended
The model held up against the monitoring data, and I proposed an EOQ-based way to size purchases as a standard for the business.

03Research and writing

Research and writing

Dissertation

Can machine data stop scrap before it happens?

Integrating Lean Six Sigma Principles with Industry 4.0 Technologies for Quantifiable Quality Management and Process Control. MSc dissertation, University of East London, submitted May 2026. Simulation study

I started from a problem I had met in production work: manual inspection catches drift too late. The university offered no route to on-site research, so I built the study on synthetic data modelled on a CNC turning process (a Jyoti 350 with a Fanuc 0i-F Plus controller).

The data pointed to spindle thermal expansion as the main cause of drift. I designed a 7-part trend logic that sends corrections to the controller through the Fanuc FOCAS interface, and tested it in a discrete-event simulation (Siemens Tecnomatix Plant Simulation) of 135,000 units. The work is aligned with IATF 16949 and ALCOA+ data-integrity requirements.

0.92 to 1.67Process capability (Cpk), simulated
97.1%Less scrap, simulated
135,000Synthetic units in the dataset

These are simulated results, not measured on a production line. The simulation assumes a stable environment and a Fanuc controller, so a real factory would see less.

Writing

I want to write about how factories lose time, material and money, and what can be done about it. The first piece is in progress.

In progressCase study

From a paper CV to one linked profile

How a printed card, a tailored CV and a portfolio site can work together as one joined-up profile, with less paper and less repeated work. I am gathering the research and sources now.

More pieces will appear here as they are finished.

04Background

Skills and education

Skills

  1. On the machineCNC turning on Fanuc and Siemens controls (Jyoti and ACE machines), choosing turning and milling tools, feeds and speeds, workholding. Materials: titanium, stainless steel and cast iron.
  2. QualitySupporting IATF 16949, ISO 9001 and ISO 14001 audits. Working with APQP, FMEA, PPAP, MSA and SPC. Finding root causes with Pareto, Fishbone and 5 Whys, and following through with NCR and CAPA. Reading GD&T.
  3. Lean5S, Kaizen, value stream mapping, TPM (CLIT) and visual management, aimed at shorter cycle times and lower cost.
  4. PlanningProduction planning and scheduling, capacity forecasting, EOQ stock sizing, risk assessment, health and safety, and writing SOPs.
  5. SoftwareAutoCAD, Excel, Word and PowerPoint, Zoho and MTTL CRM, and Siemens Tecnomatix Plant Simulation (used in my dissertation).
  6. LanguagesEnglish and Telugu (native).

Education

QualificationInstitutionDates
MSc Mechanical Engineering with Industrial Placement YearAutomation and Robotics, Smart Industries and Digital Manufacturing, Structural Dynamics and Stability.University of East LondonJan 2025 – Jan 2027
BTech Mechanical EngineeringMetal Cutting and Machine Tools, Production Technology, Production Planning and Control. Final-year project: energy harvesting with piezoelectric transducers.NRI Institute of Technology, Agiripalli, India2015 – Apr 2018

Short courses Six Sigma fundamentals (online course) · Design for Manufacturing Fundamentals (Geomiq Academy)

05Enquiry

Hiring, or just want to talk?

Tell me about the role and I will reply by email. You can also use the details at the bottom of the page.

How I use your details

I am Madupalli Venkata Krishna Rao, and I will use the details you enter here only to reply to your enquiry. They are sent to me by email and stored in my form inbox with Netlify, which hosts this site and may process data outside the UK. I will not add you to a mailing list or share your details with anyone else. I will delete your enquiry once the conversation is finished, or sooner if you ask. To ask about, correct or delete your details, email connect@mvkr.co.uk.

NameMadupalli Venkata Krishna Rao
London, UK
Emailconnect@mvkr.co.uk
LinkedInlinkedin.com/in/vkr-madupalli
Updated 27 Oct 2026
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