Software Development

KNA develops applications around workflows, users, and data requirements. Projects can include web, Windows, and Android applications, industrial dashboards, or software connected to machines. The focus is usable functionality that fits existing operations.

Scopes include production records, field inspections, quality control, maintenance, inventory, reporting, and approval workflows. User roles, inputs, process rules, and expected outputs are mapped before development.

Software can display machine status, runtime, alarms, counters, measurement history, and process indicators. Indicator definitions, data sources, units, sampling intervals, and missing-data handling are discussed so the interface does not mislead users.

Data can be stored for search, trends, exports, reports, and engineering analysis. MATLAB or other analytical tools may be used as appropriate. AI analysis or predictive maintenance requires suitable data and a separate evaluation; collecting data alone does not create predictive capability.

Applications can communicate with PLCs, microcontrollers, HMIs, data loggers, industrial PCs, and gateways. Integration with ERP, MES, databases, or existing applications starts with available APIs, protocols, data formats, and access permissions. Working systems do not need to be replaced wholesale.

• APIs, MQTT, industrial communications, synchronization, and data exchange between systems.
• PostgreSQL, MySQL, Firebase, Node-RED, and Grafana can be selected according to requirements.
• Local, server, cloud, or Docker deployment is chosen to suit operations and system management.

KNA can add AI capabilities to web, Windows, and Android applications around user needs. Development starts with the function to support, data permitted for use, and how results will be evaluated. Models or AI services are selected for the application and its integration with existing systems.

Data access, review of results, service usage costs, and error handling are discussed before implementation. AI capabilities are tested against agreed requirements; their results are not assumed to be correct in every case. Camera analysis and visual inspection are covered in the AI & Image Processing service.

Design covers authentication, permissions, input validation, data management, error handling, and backup and recovery requirements within scope. Operator interfaces need to communicate system status, action results, and conditions requiring attention.

Modular structure and clear interfaces support future changes. Microservices, cloud services, or additional technologies are used when operational requirements justify them. Testing covers user workflows, integrations, data, and agreed failure conditions.

Work starts with workflow examples and data cleared for use, followed by design, development, user review, testing, and deployment. Documentation, source code, licenses, user training, and post-handover support must be specified in scope rather than assumed.

For an initial inquiry, explain who will use the application, the problem to solve, devices or systems to connect, data volume, access requirements, and timing. Photos, diagrams, or sample reports can be sent by email or WhatsApp.