📍 Johannesburg, South Africa
📫 nk.fuze@gmail.com | 🔗 LinkedIn | 🌐 kennethngcobo.com

I am an experienced Software and Electronics Engineer with a strong track record in full-stack web development and embedded systems. I specialize in building scalable web applications and consulting in the LED lighting industry, offering complete lifecycle services from concept to production.

With a passion for innovation and teaching, I also design and coach software development courses, fostering industry-aligned, future-ready skills.

I developed a comprehensive Inventory and Job Management System using Vue.js, Node.js, and MySQL, designed to streamline component tracking, job kitting, and procurement processes. The system supports bulk importing of component data from existing Excel records, storing details such as quantity, price, and supplier information in a structured MySQL database.

• Real-time search with auto-suggestions on the front end for quick component lookup.
• BOM (Bill of Materials) uploads, which dynamically deduct components from stock when assigned to jobs.
• Job kitting integration with barcode scanning:
  • Components are scanned via a scanner connected to a Raspberry Pi.
  • The scanner communicates with the system using WebSockets, enabling real-time stock updates.
• Low stock alerts, which automatically notify buyers when components fall below threshold levels.
• Supplier purchase order (PO) generation, with tracking of expected delivery dates (ETAs).
• Job ETA estimation, factoring in missing components, their POs, and ETAs to provide accurate forecasting.

This system significantly improved operational efficiency, enhanced inventory accuracy, and optimized procurement and production planning workflows.

I developed QuoteLink, a middleware system that seamlessly integrates the company’s quoting platform (SFA) with its ERP system (Sage) to eliminate redundant data entry, reduce human error, and accelerate sales order processing. The platform was built with React, Node.js, Microsoft SQL Server, SMTP email services, and secured with user authentication.

SFA enabled users to easily build custom lighting product quotes by selecting categories, wattages, beam angles, and other options. It generated custom item codes and calculated prices based on selected configurations. However, users then had to manually check Sage for existing codes or create new ones, and manually re-enter item details to generate a sales order — a time-consuming and error-prone process, especially for large quotes.

• Quote import:

  • User enters the SFA quote number into QuoteLink.
  • The system retrieves all quote data directly from the SFA database.

• Item code validation:

  • Automatically checks if generated item codes exist in Sage.
  • Highlights any missing codes, which can be requested with a single click.
  • Sends a notification to the responsible team to create the missing codes.

• Automated SO creation:

  • Once all codes are confirmed, the user can generate a Sales Order (SO) in Sage with:
    • Correct item codes
    • Quantities and prices
    • Customer details
  • The production team is notified of the new SO for scheduling.

• Error elimination:

  • Fully removes the need to retype or manually transfer quote information into Sage.
  • Reduces processing time and improves accuracy in order fulfillment.

QuoteLink became a critical link in the company’s sales-to-production pipeline, improving efficiency, accuracy, and internal coordination across quoting, ERP, and manufacturing teams.

I developed QCTrack, a digital quality control system tailored for a lighting manufacturing company to log, manage, and analyze product non-conformance issues, whether identified internally or returned from the field. The platform streamlined issue tracking, accountability, and root cause analysis, significantly improving traceability and process improvement efforts.

• Issue logging interface for relevant staff to report non-conformances:

  • Attach images and provide detailed descriptions.
  • Select from a predefined list of common fault categories for consistent classification and future analysis.
  • Identify the responsible department (e.g., Technical, Mechanical Design, Production).

• Automated email notifications sent to the assigned individuals within the responsible department, including fault details and images.

• Root cause analysis workflow:

  • Responsible parties provide cause investigation, preventative measures, and cost tracking (e.g., replacement components).
  • Issues can be attributed to categories such as supplier error or production procedure fault.
  • If supplier-related, their details are logged for follow-up.

• Issue closure validation ensures that all required fields are completed before an issue can be marked resolved.

• Auto-generated QC reports:

  • Upon closure, a PDF report is automatically created and emailed to the original reporter.
  • Includes all relevant data, including client information for traceability and customer communication.

• Interactive analytics dashboard:

  • Filter and visualize data to identify trends by product, fault type, or supplier.
  • Interactive bar charts allow users to click on a product or category to view associated issues.
  • Used actively in QC meetings and ISO audits to demonstrate issue resolution processes and trend tracking.

Built with a stack including Nuxt.js, Node.js, MySQL, and an integrated SMTP email service, QCTrack became a core part of the company's quality assurance and continuous improvement strategy.

I developed LumaTest, a centralized lab scheduling and reporting system for a lighting manufacturing company with in-house photometric, thermal, and IP testing labs. The platform was built with Nuxt.js, Node.js, MySQL, and an integrated SMTP email server to streamline internal test requests, communication, and data access.

• Test booking interface for internal stakeholders across departments to schedule tests with specific labs.
• Mandatory input of fixture specifications (e.g., wattage, length, CCT, CRI) to eliminate ambiguity about which variant was tested.
• Users specify expected result dates and test priorities, which are stored in the database and reflected on the lab's shared schedule.
• Automated email notifications to lab technicians upon new test requests.
• Lab technicians can:
  • Review their schedule and respond with a revised promise date if needed.
  • Trigger email updates to the requester with the new timeline.
• Live lab schedules visible to all relevant stakeholders, allowing departments to negotiate and adjust priorities collaboratively.
• Upon test completion:
  • Technicians upload test reports and mark tests as pass/fail.
  • The system sends an automated email with the test report to the requester.
• A centralized, searchable and filterable test report archive eliminates the need for manual file browsing across network folders.

LumaTest significantly improved internal coordination, reduced miscommunication, and streamlined access to historical testing data across the organization.