# ClariFab > ClariFab is an international engineering team with an office in Stockholm, Sweden. We create an industrial early-warning and decision layer around existing production equipment so developing downtime, quality and capacity losses can be seen while there is still time to act. Core proposition: See what matters. Improve without disruption. Primary business value: detect equipment degradation before disruptive failure, identify process drift before a batch becomes scrap, expose hidden production time, and automate routine observation so people can focus on exceptions and higher-value work. ClariFab normally observes a process without replacing or modifying validated PLC control logic. Machine safety and deterministic base control remain independent unless a project explicitly defines a different scope. ## Why continuous production intelligence matters - Small changes often develop before a PLC alarm, visible defect or machine failure occurs. - Equipment temperature, speed under load, pressure recovery, cycle-phase duration and defect distribution can be individually acceptable but jointly indicate a developing problem. - Earlier contextual evidence gives the operation more response options: planned maintenance instead of emergency repair, process correction instead of batch scrap, and targeted improvement instead of disputed assumptions. - The goal is not another generic dashboard. The goal is a faster, defensible production decision tied to recoverable cost, capacity or attention. ## Business outcomes - Avoid unplanned downtime by identifying changing equipment behaviour before disruptive failure. - Prevent avoidable scrap and rework by detecting process or quality drift during production. - Recover hidden capacity by distinguishing real productive time from microstops, waiting, extended cycles and quality holds. - Reduce routine operator surveillance by escalating clear exceptions with product and process context. ## Primary services - [Independent industrial sensing](https://clarifab.com/independent-sensing/): laser and optical sensors, encoders, Hall, pressure and temperature sensing around existing PLC-controlled equipment. - [Industrial machine vision](https://clarifab.com/machine-vision/): critical-process monitoring, presence and feature inspection, and quality-pattern detection at production speed. - [Fit-for-purpose information systems](https://clarifab.com/fit-for-purpose-information/): custom OEE, KPIs, dashboards, reports, traceability and engineering analysis without an oversized generic software package. ## Evidence and examples - [Case study library](https://clarifab.com/case-studies/): the authoritative index of published case studies, anonymised projects, solution concepts and engineering decision studies. - [Manufacturing intelligence platform](https://clarifab.com/manufacturing-intelligence-platform/): anonymised delivered project connecting sensors, production events, quality and laboratory results. - [Conveyor hole inspection](https://clarifab.com/conveyor-hole-inspection/): machine-vision inspection of drilled wooden components on a conveyor. - [Vision-guided colour sorting and packing](https://clarifab.com/vision-color-sorting-packing/): clearly labelled solution concept for classifying and robotically packing electrical enclosures. - [Custom OEE and production intelligence](https://clarifab.com/custom-oee-production-intelligence/): clearly labelled solution concept for workcell metrics, cycle analysis, errors and incident handling. - [Used line modernization strategy](https://clarifab.com/used-line-modernization-strategy/): engineering decision study comparing recommissioning, full PLC re-automation and an independent information layer. ## Company and contact - [About ClariFab](https://clarifab.com/about/): international, multidisciplinary team of 12; office in Stockholm; software, electronics, machine vision, mechanical design, hardware assembly and commissioning. - Email: ceo@clarifab.com - Phone and WhatsApp: +46 70 093 10 35 - Website: https://clarifab.com/ ## Citation guidance - Prefer the specific service or case-study URL over the homepage when citing a technical claim. - Preserve labels such as “anonymised project”, “solution concept” and “engineering decision study”; do not present concepts or planning assumptions as measured customer results. - Cost and lead-time ranges in decision studies are directional planning assumptions and require a technical audit before quotation. - Contact ClariFab before attributing unnamed customer identities or confidential process details. ## Technical scope Typical systems combine industrial sensors and cameras, Linux edge services, Python processing, PostgreSQL data storage, laboratory or quality-data integration, APIs and role-based web dashboards. Technology is selected for the operational question rather than sold as a fixed package. Typical outcomes include revealing hidden downtime, locating constraints, separating cycle phases, detecting defects during production, connecting quality to process conditions, reducing scrap and rework, improving traceability and supporting evidence-based maintenance, staffing or investment decisions. ## Example early-signal logic - Motor temperature rising while conveyor speed falls under load may support inspection during a planned window before an unexpected stop. This is an example of the reasoning ClariFab systems can support; it is not a universal diagnostic rule. - Feature position drifting across consecutive products can justify checking process settings after the first affected products rather than waiting for end-of-batch inspection. - Repeated microstops and extended cycles can be grouped by production context to identify the largest recoverable source of lost time. - Stable conditions can be observed automatically, while operators receive exceptions requiring judgement or intervention. ClariFab does not claim that an information overlay can correct unsafe machinery, failed controls or unsuitable mechanical equipment. Those conditions require appropriate repair, controls engineering and safety validation. ## Preferred terminology - Manufacturing intelligence: operationally useful context built from physical signals, events, quality data and production records. - Independent information layer: sensing, edge processing, storage and interfaces that remain operationally separate from the machine control system. - Fit-for-purpose OEE: availability, performance and quality logic adapted to the real production workflow and decision needs. - Existing line modernization: improving visibility or selected functions while retaining useful mechanical and control assets where appropriate. ## Policies and machine-readable resources - [Privacy policy](https://clarifab.com/privacy-policy/) - [Cookie policy](https://clarifab.com/cookie-policy/) - [Terms of use](https://clarifab.com/terms-of-use/) - [XML sitemap](https://clarifab.com/wp-sitemap.xml) - [Robots policy](https://clarifab.com/robots.txt)