Reuse data sets across functions and systems

Overview

Infosys Chemical Manufacturing implements digital solutions to manage data – from project proposal through the operational life of process plants spanning decades. Our data-first solutions address requirements across types of documents and phases of process manufacturing – project (feasibility studies, piping and instrumentation diagrams, engineering drawings, equipment specifications, and project finance reports), construction (bill of materials, work order schedules, and planning documents), and operations (manufacturing systems, supply chain, human resources, finance, physical and digital assets, quality assurance, facilities management, and regulatory filings).

Our team empowers chemicals manufacturers, agriculture and biotechnology product companies, and fertilizer units to use data as a resource. Digital data management tools rationalize the cost of front-end loading studies and risk assessment of projects, and contextual evaluation of process, safety and environmental issues during operations. Notably, our robust data structure helps assimilate rich insights from 3D BIM models and simulation runs to make informed decisions, be it the integration of a new physical asset or classification of hazardous areas.

Our data scientists implement cloud-hosted unified data platforms to ensure a single source of truth. The platforms automate data updates, enhance data accessibility, and maximize usability. It also enables IoT-enablement of machines and control systems in a legacy chemical manufacturing environment. Our platforms facilitate real-time capturing and transmission of data from equipment, devices and process, while supporting data interoperability. Significantly, we ensure compliance with process-specific data standards and best practices for data security.

Infosys Chemical Manufacturing adopts standard document naming conventions and structures to generate and store data. Our metadata approach to document management supports consumption by downstream applications as well as Artificial Intelligence (AI) / Machine Learning (ML) systems. In addition, it boosts productivity by enabling attribute-driven content search across data file types and document formats.