ConvergencePro

ConvergencePro darbina ar Atos

Atos ir pasaules līderis digitālās transformācijas jomā ar aptuveni 78 000 darbinieku un gada ieņēmumiem aptuveni 10 miljardi eiro apmērā. Eiropas pirmā vieta kiberdrošības, mākoņdatošanas un augstas veiktspējas skaitļošanas jomā, grupa piedāvā pielāgotus visaptverošus risinājumus visām nozarēm 68 valstīs. Atos, kas ir dekarbonizācijas pakalpojumu un produktu pionieris, ir apņēmies nodrošināt drošu un dekarbonizētu digitālo līdzekli saviem klientiem.<br/>Siemens un Atos 2011. gadā izveidoja stratēģisko globālo aliansi, iezīmējot veiksmīgas sadarbības sākumu, kuras mērķis ir veicināt inovācijas un sniegt vērtību dažādās nozarēs. Kopš 2020. gada Atos ir paplašinājis sadarbību ar globālo partnerību ar nozares vadošo zema koda lietojumprogrammu izstrādes platformu Mendix™.

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Kāpēc Deriving insights from the convergence of OT and IT data.?

ConvergencePro empowers operational teams with real time insights, enabling swifter, data supported decision making in line with business objectives. The ability to incorporate multiple data sources provides an extensible core platform, enabling a singular focus for operational teams.
ConvergencePro facilitates the synergy of IT and OT data allowing new insights to be derived from previously siloed data repositories.

An engineer reading assembly line data on a tablet

Priekšrocības

Whole factory observability within a central dashboard, empowering the factory with visibility across the entire production process. Dashboards can capture what truly matters to the factory team, e.g., highlighting operational issues, financial impacts, or atmospheric abnormalities.
True data convergence with the ability to ingest from multiple sources that can pass data through standard API connectivity. Data is overlayed in a single view or series of views in accordance with business priorities to drive meaningful insights upon which decisions can be based and supported.
Automated support process integration with standard ITSM platforms via open API connectivity. This mitigates/removes the loss of valuable production time due to ineffective issue management, replication of support activity, or problems identifying the correct team to work on the problem.
Automated alert correlation across equipment, in line with business-driven prioritisation. Prevents multiple tickets being raised for a production line when the issue is with one key piece of equipment. The right information is delivered to the right support team enabling swift resolution of issues.
GenAI integration enables ingestion of contextual information about factory environments including machine manufacturer data, local site operational procedures, and knowledge base articles. This enables the service to diagnose and provide a synopsis of the issue, and proposed resolution strategy.

Piedāvātās iespējas

Prioritised dashboard insights through custom views

The central observability dashboards can be tailored to suit the different users/groups monitoring the system. This allows, for example, factory management to focus on financial impact and business consequences, and technology support teams to see operational equipment issues.

Worker in safety gear using tablet in warehouse

Near real-time alerting of issues in production

Alerts from production equipment are trapped and correlated against CMDB data to establish a rich picture of the impacted asset, and associated assets. This impact, severity, and the cause are then presented on the dashboard with other business critical metrics such as real-time financial impact.

Worker using tablet near industrial robot

Automated ticket creation based on data correlation

Tickets are created in the standard ITSM tool, populated with relevant information, and routed to the correct resolver group based on the standard mappings defined in the ITSM platform. This removes the time lost between an issue occurring, and a technician reporting the problem in the system.

Worker monitoring robotic arms in factory

Integrated AI for issue diagnosis and solution proposal

Identified issues are analysed to produce a synopsis of the problem which is added to the support ticket. GenAI leverages previously ingested contextual data about the factory, common incidents, and historical records to provide a proposed resolution to the problem, again within the support ticket.