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Automating legacy systems in manufacturing using AutoHotkey and Python for streamlining production workflows.

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Internship @Kiara Jewellery Pvt. Ltd.

Kiara Jewellery Private Limited is a part of the Dalloz group which is a major player in the Luxury goods industry. A specialist in unique European designed fine jewellery. With over a decade of experience, it's a best in class company in the casted jewellery category. Ideal partners for businesses looking for a globally competitive vendor.

Problem Statement & Solution 1

At a multinational jewellery manufacturing company, a legacy software system was used to track stock, locations, and related details. Jewellery production involved multiple steps—filing, setting, polishing, etc.—and after each step, job cards accompanying the jewellery were handed to data entry personnel. These job cards included jewellery details and worker codes, requiring manual entry into the system. Processing a batch of 15–20 job cards took at least 1.5 minutes per card, involving 200–250 clicks and extensive typing of specific codes. Four employees were dedicated to this task.

To optimise this, I used AutoHotkey, a scripting language often employed for automating tasks in games, to create a script that acted as an overlay on the legacy software. This script replicated the data entry process, automating all actions on the screen. I meticulously recorded click coordinates and wrote a 243-line script. With this solution, workers could directly scan the job card's QR code and their worker barcode at a PC, eliminating manual data entry, reducing inefficiencies, and removing the need for a queuing system. The process became so user-friendly that anyone could perform the entry.

Problem Statement & Solution 2

Another time-intensive process involved uploading large 46–50-page PDF order files from retail clients. These PDFs contained specific details—order numbers, styles, carat, etc.—which employees manually converted to Excel and modified over 20 minutes per file to make them compatible with the legacy system, often leading to errors. To address this, I wrote a Python script allowing users to upload the PDF. The script automatically converted, formatted, and fabricated the data into an uploadable format within seconds, ensuring 100% accuracy and saving significant time.

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Automating legacy systems in manufacturing using AutoHotkey and Python for streamlining production workflows.

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