Canlitek Private Solutions is a Chennai service company working across both service management and manufacturing, including the deployment of optical fibre cable.
The machinery involved in those operations is monitored through IoT automation — measured, analysed and optimised in real time — and the ERP work was to put that alongside the rest of the business rather than next to it.
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Canlitek runs service management and manufacturing on one customised Odoo system, with IoT-based automation feeding machinery data into it. Contacts, employees, inventory, purchase, sales, service and accounts sit on one database, and the machinery monitoring that was already central to the business connects to it instead of standing on its own.
A business that both services machinery and manufactures is the same shape as a business that both sells and services: the expensive failures happen at the handover, so the argument for one database is about the boundary rather than about any one department.
Taken from the project itself rather than from a capability list.
ERP across contacts, employees, inventory, purchase, sales, service and accounts, with IoT-based automation for machinery monitoring.
Odoo ERP implementation with customisation and IoT automation
Chennai, India
See every Odoo implementation case study, or the full Odoo ERP implementation service.
A great deal of productive time was going into routine human intervention at various stages of the operation. The business wanted that bottleneck removed so its people could work on strategy instead of on handovers.
Steps that existed only to move information from one part of the process to the next consumed time that was not buying anything.
Service and manufacturing were run as two operations. Anything that touched both — a customer, a part, a technician — existed twice.
Machinery was already being measured and analysed in real time, but that data was not connected to the system holding the contracts, the stock and the people.
Deploying optical fibre cable needs the right people and the right instruments on site. Without a record of either, that is arranged by phone call.
Machinery degradation and failure were dealt with when they happened rather than anticipated, even though the data that could anticipate them was being collected.
The implementation covered contacts, employees, inventory, purchase, sales, service and accounts, plus the IoT automation, because the operation it had to describe spans service and manufacturing at once.
Service operations on the same database as the rest of the business, so a job is raised, assigned, executed and billed against one record rather than three.
Parts and consumables held as stock, bought against real demand from the service and manufacturing sides alike. See Odoo Inventory.
The people doing the work on the system that holds the work, so the workforce on a deployment is a record rather than an arrangement. See Odoo HR.
Customers and the commitments made to them — including maintenance contracts — in one place, with their history attached.
Invoicing and the books on the same data as the jobs and the stock, rather than assembled from them afterwards. See Odoo Accounting.
IoT-based automation for AMC and CMC work, and predictive analytics against the centralised data to anticipate machinery degradation and potential failures.
Service and manufacturing run on one database, with the machinery data that was already being collected connected to it. The routine handovers that used to need a person are handled by the system.
contacts, employees, inventory, purchase, sales, service and accounts together.
the maintenance contracts supported by the machine data itself.
machinery degradation and potential failures anticipated from centralised data.
the people and instruments for a deployment tracked through the same system.
the service side and the manufacturing side reading the same records rather than their own.
What the client reports back, in their terms. We publish no percentages here because the project did not measure any, and a number we cannot stand behind is worth less than one we can.
Routine human intervention between stages stopped being the way information moved, which was the reason the project started.
Service and manufacturing share customers, parts and people, and now share the record of them.
Automation for AMC and CMC work, built on the machinery monitoring that was already in place.
Predictive analytics against centralised data, so machinery degradation is seen coming rather than reported after the fact.
The people and the testing instruments for optical fibre deployment tracked and allocated through the system.
The stated aim: people working on how the business should develop rather than on moving information between stages.
What this implementation used, written up properly.
Project, service and manufacturing in one engineering business.
Work orders, routings and what the shop floor actually reports.
Network deployment, field work and the assets behind it.
Employees, attendance and the workforce record behind field work.
Connecting Odoo to the systems and devices that feed it.
Custom modules built to survive version upgrades.
If you are running service and production as two systems, or collecting machine data that nothing downstream uses, tell us what the operation looks like. We will say what configuration can reach and what would need building, and the diagnosis call is free.
