Vulcan Advance Intelligence Computing Pvt. Ltd.

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Vulcan Advance Intelligence Computing Pvt. Ltd. tightened shop-floor control with a centralised workflow

A practical shift from WhatsApp/Excel coordination to trackable daily execution.

57%

Reduction in daily coordination time for plastics work

57%

Reduction in daily coordination time for plastics work

21%

Reduction in excess inventory across store and production

21%

Reduction in excess inventory across store and production

6→2 days

Improvement in order-to-dispatch lead time with fewer last-minute follow-ups

6→2 days

Improvement in order-to-dispatch lead time with fewer last-minute follow-ups

Vulcan Advance Intelligence Computing Pvt. Ltd. at a glance

Vulcan Advance Intelligence Computing Pvt. Ltd. is a micro plastics manufacturing unit based in Ghaziabad. Their day-to-day work involves coordinating orders, material availability, production execution and dispatch commitments. Earlier, updates were shared through a mix of Excel sheets, calls and WhatsApp, which made it hard to keep everyone aligned. By moving to a centralised workflow, the team standardised handovers, reduced rework in reporting, and improved execution predictability.

Plastics

Industry

Plastics

Industry

Micro

Company Size

Micro

Company Size

Ghaziabad, India

Location

Ghaziabad, India

Location

Stock accuracy across stores and production bins

Use Cases

Stock accuracy across stores and production bins

Use Cases

Challenges

QC holds were not reflected in available stock, leading to accidental usage.

Production plan changed multiple times a day due to capacity conflicts and material gaps.

Short/excess at dispatch led to urgent rework and multiple trips between store and floor.

Implementation: Centralised workflow with clear owners

Earlier, QC holds and rework notes were kept on paper and were not visible to planning. This broke down during rejections; without traceability, isolating root cause took days and blocked dispatch. We implemented a single system of record connecting sales, purchase, production and dispatch so everyone worked off the same status. QC marked holds against lots, and planners saw only cleared stock as available for production. It also made owner reviews easier because key exceptions were visible without chasing the team. The practical outcome was that teams stopped re-entering the same data and acted on exceptions early.

Controlling rework through traceability and holds

Earlier, the daily plan was decided in fragments—by urgency, not by capacity and material signals. This broke down as soon as urgent orders came in; jobs were half-started and WIP piled up across stages. We implemented a single system of record connecting sales, purchase, production and dispatch so everyone worked off the same status. Planning moved to a simple daily schedule linked to orders, capacity and material, reducing last-minute reshuffles. The practical outcome was fewer escalations, faster decisions, and dates that changed less often.

Stabilising planning with live WIP and material signals

Earlier, dispatch readiness depended on people coordinating invoice, packing and transporter on calls. This broke down when transporter slots moved; finished goods were ready but paperwork and packing lagged behind. We implemented structured stage-wise tracking and checklists so work moved forward only when prerequisites were met. Dispatch checklists were run a day ahead so invoicing, packing and transporter booking stayed aligned. The practical outcome was fewer escalations, faster decisions, and dates that changed less often.

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