KOYNA ENGINEERS PVT LTD
KOYNA ENGINEERS PVT LTD
KOYNA ENGINEERS PVT LTD
KOYNA ENGINEERS PVT LTD tightened shop-floor control with a centralised workflow

KOYNA ENGINEERS PVT LTD tightened shop-floor control with a centralised workflow

KOYNA ENGINEERS PVT LTD tightened shop-floor control with a centralised workflow

Turning daily follow-ups into a repeatable workflow across departments.

24%

Reduction in daily coordination time for engineering work

24%

Reduction in daily coordination time for engineering work

29%

Reduction in excess inventory across store and production

29%

Reduction in excess inventory across store and production

8→3 days

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

8→3 days

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

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How KOYNA ENGINEERS PVT LTD operates

How KOYNA ENGINEERS PVT LTD operates

KOYNA ENGINEERS PVT LTD is a medium engineering manufacturing unit based in Nashik. 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.

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Engineering

Industry

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Engineering

Industry

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Medium

Company Size

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Medium

Company Size

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Nashik, India

Location

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Nashik, India

Location

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Centralised purchase & vendor performance tracking

Use Cases

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Centralised purchase & vendor performance tracking

Use Cases

Challenges

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

No simple view of vendor-wise delays, so the same issues repeated every month.

Job-work material sent out was tracked in registers; return quantity and shortages were unclear.

Before: Too many moving parts, no single view

Before: Too many moving parts, no single view

Before: Too many moving parts, no single view

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.

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.

Reducing month-end surprises with traceable transactions

Reducing month-end surprises with traceable transactions

Reducing month-end surprises with traceable transactions

Earlier, vendor follow-ups were call-driven and depended on whoever remembered to push. This broke down during peak load—approvals got delayed and committed dates slipped without a simple exception view. We implemented a centralised workflow where each order, material requirement and update had a clear owner and timestamp. The purchase team used one follow-up queue, logged committed dates, and escalated exceptions early. Over time, the team built confidence because the numbers matched what they saw on the floor. The practical outcome was that teams stopped re-entering the same data and acted on exceptions early.

Earlier, vendor follow-ups were call-driven and depended on whoever remembered to push. This broke down during peak load—approvals got delayed and committed dates slipped without a simple exception view. We implemented a centralised workflow where each order, material requirement and update had a clear owner and timestamp. The purchase team used one follow-up queue, logged committed dates, and escalated exceptions early. Over time, the team built confidence because the numbers matched what they saw on the floor. The practical outcome was that teams stopped re-entering the same data and acted on exceptions early.

Controlling rework through traceability and holds

Controlling rework through traceability and holds

Controlling rework through traceability and holds

Earlier, job-work material movement was tracked in registers and return status was unclear. This broke down on returns; shortages and rate differences led to repeated reconciliations. We implemented structured stage-wise tracking and checklists so work moved forward only when prerequisites were met. Material sent out and received back was logged against job-work orders, making shortages visible immediately. The practical outcome was fewer escalations, faster decisions, and dates that changed less often.

Earlier, job-work material movement was tracked in registers and return status was unclear. This broke down on returns; shortages and rate differences led to repeated reconciliations. We implemented structured stage-wise tracking and checklists so work moved forward only when prerequisites were met. Material sent out and received back was logged against job-work orders, making shortages visible immediately. The practical outcome was fewer escalations, faster decisions, and dates that changed less often.

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