Welcome to Bika Fire Assay
Fika Fire Assay Demonstration installation. Open Source LIMS for mines and geochemistry
Request Access ᐧ Dashboard ᐧ BrochureBika Open Source LIMS, established in 2002, is a feature-rich, mature, web-based LIMS, 'better than any boxed product'. Through the benefits of Open Source, Bika presents a feasible alternative to expensive proprietary systems.
Bika Fire Assay is built as an add-on to Bika's standard LIMS, which does chemistry very well, to ISO 17025 standard. Bika's flexible configuration enables its geochemistry capabilities. Most labs only interface their instruments and set the rest up for a good fit. Bika LIMS is not expensive, there are no license fees, only services as implementation costs: Installation, Configuration, Training, Start-up Assistance, Go Live. Complex setup data and Instrument interface customisation add to it, but a standard Implementation can be completed for $15k for medium-sized laboratories. Less, depending on urgency and staff making use of online content and assistance, albeit at a slower pace. Pages 6 - 8 in our brochure discuss how to navigate Open Source projects most affordably. Please let me know if you have questions or are interested in access to our online demo or a live demonstration. Bika = Senaite+Bika Lab Systems contributes to the Senaite core and maintains the Bika brand from Cape Town, as a skin of add-on customisations and configurations.
Bika LIMS is FOSS, Free and Open Source. Labs get full ownership of the system and are free to customise it using their own resources. There are no license fees, no vendor lock-in, a free upgrade path, and it can be used by unlimited users. In this installationConfigured for geochemistry testing, on sample types such as Run of Mine, Rock, Core, Pulp, Residue, Sediment, Concentrate and Water
Analyses are configured in categories for Preparation, Physical, PSD, Fire Assay, Digestion, Au Aqua Regia, Au Fire Assay, Elements FA F-AAS, GF-AAS, ICP-MS, ICP-OES and XRF.
Grades are configured as analysis specifications and applied to results per Sample Type and users alerted to out of range results.
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