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Glossary Tag: process monitoring

  • Read-only integration

    Read-only integration commonly refers to a connection between systems in which one system can access, query, or receive data from another system without being allowed to create, update, or delete records in the source system.

    In manufacturing and regulated operations, this usually means an application such as MES, reporting, analytics, quality, or dashboard software can pull or display data from ERP, PLM, historians, equipment systems, or other business applications, but cannot write changes back through that same integration path.

    What it includes and excludes

    A read-only integration can include data retrieval methods such as API calls, database views, file exports, replicated datasets, or reporting connectors, as long as the consuming system has no permission to modify the source records through that interface.

    It does not mean the data itself is static or unchangeable. The source system may still be updated by authorized users or other interfaces. Read-only only describes the permissions and behavior of the integration path.

    How it appears in operations

    • An MES displays item masters, routings, or order data pulled from ERP but cannot alter ERP records.

    • A quality reporting tool reads inspection or nonconformance data for analysis without changing the original quality records.

    • A plant dashboard reads machine, batch, or production status data from source systems for visibility only.

    This approach is often used when organizations want visibility, reporting, or cross-system context while limiting the risk of unintended changes in systems of record.

    Common confusion

    Read-only integration is often confused with one-way integration. They are related but not identical. One-way integration describes direction of data flow. Read-only describes permission level. A one-way feed is often read-only from the receiver’s perspective, but the terms are not exact substitutes.

    It is also commonly confused with view-only access. View-only access usually refers to a user interface or user role, while read-only integration refers to a system-to-system data connection.

  • Time bucket

    A time bucket is a fixed time interval used to group planning or performance data into manageable periods. In manufacturing and supply chain systems, time buckets commonly refer to units such as hours, shifts, days, weeks, or months that are used to organize demand, inventory, production, capacity, or schedule information.

    The term usually applies to planning and reporting logic rather than to the physical process itself. For example, an ERP or MES may summarize orders, labor, machine load, or output by day or by shift. The bucket defines how time-based data is collected, stored, compared, or displayed.

    Where it appears

    • Production planning: forecasted and scheduled quantities may be grouped into daily or weekly buckets.

    • MRP and supply planning: supply and demand are often netted within specific bucketed periods.

    • Capacity planning: available hours and required load may be compared by shift, day, or week.

    • Performance reporting: throughput, downtime, scrap, or labor usage may be trended by defined intervals.

    What it includes and excludes

    A time bucket includes the start and end boundaries of a reporting or planning interval and the data assigned to that interval. It does not by itself define sequencing, priority rules, or real-time event timing. A bucketed schedule is a summarized view of time, not the same thing as an exact timestamped execution record.

    In practice, smaller buckets allow more detailed planning but require more data and maintenance. Larger buckets provide a broader planning view but can hide short-term variation.

    Common confusion

    Time bucket vs. timestamp: a timestamp marks a specific moment, while a time bucket groups many events or quantities into a defined period.

    Time bucket vs. scheduling horizon: the scheduling horizon is the total future period being planned, while the time bucket is the size of each interval within that horizon.

    Time bucket vs. time fence: a time fence is a rule boundary for planning changes, not the interval used to aggregate data.

    Manufacturing example

    A planner may review weekly demand in ERP, then break the current week into daily or shift-based buckets in MES to align production capacity and work-center loading more closely to shop-floor reality.

  • User interface (UI)

    User interface (UI) commonly refers to the visible and interactive part of a software system, device, or machine that a person uses to view information, enter data, and trigger actions. It includes screens, menus, buttons, forms, icons, labels, and other controls that shape how a user interacts with the underlying application or equipment.

    In manufacturing and regulated operations, a UI may appear in MES screens, ERP forms, electronic work instructions, quality records, HMIs, maintenance applications, dashboards, and mobile operator apps. The UI presents information from the system and captures user input, but it is not the same thing as the business logic, database, workflow engine, or system integration behind it.

    What it includes

    • Visual layout of screens and pages
    • Input fields, buttons, menus, filters, and navigation
    • Status indicators, alerts, prompts, and messages
    • Role-based views for operators, supervisors, quality staff, or maintenance teams
    • Device-specific presentation such as desktop, tablet, panel PC, or handheld screens

    What it does not mean

    UI does not usually mean the full user experience, training approach, or process design. It also does not mean the underlying application architecture or data model. In OT environments, UI can overlap with an HMI, but the terms are not always interchangeable. An HMI usually refers more specifically to the operator-facing interface for controlling or monitoring industrial equipment, while UI is the broader term for any human-facing software interface.

    Common confusion

    UI vs. UX: UI is the interface itself, while UX refers to the broader experience of using the system, including clarity, efficiency, and ease of completion.

    UI vs. HMI: HMI is typically used for machine or process interaction in industrial settings. UI can refer to HMIs, but also to enterprise and shop floor software screens that are not direct machine controls.

    UI vs. front end: Front end often refers to the technical implementation layer of the interface. UI refers to the human-facing interface as used and seen.

    How it shows up operationally

    In day-to-day workflows, the UI is where users acknowledge tasks, review work instructions, enter production data, record inspections, sign off steps, or investigate exceptions. For example, an MES UI might show routing steps, required material lots, and data entry prompts for in-process checks, while a quality UI might present nonconformance details and disposition fields.

  • Use-As-Is Disposition

    Use-As-Is Disposition commonly refers to a formal decision to accept a nonconforming material, component, or product for its intended use without rework, repair, or scrap. It means the item is released in its current condition after review determines that the observed nonconformance does not prevent acceptable use within the applicable requirements or approved decision process.

    In manufacturing and quality workflows, this disposition appears as one possible outcome of nonconformance review. It is typically recorded in an NCR, deviation, concession, or MRB-related process, along with the reason for acceptance, scope, affected items or lots, and required approvals. The term refers to the decision status itself, not to the investigation or corrective action process that may exist alongside it.

    What it includes and excludes

    • Includes: acceptance of an item in its current state for defined use, with documented review and disposition.
    • Excludes: changing the item to meet requirements. If work is performed to bring the item into conformance, that is rework or repair, not use-as-is.
    • Excludes: automatic acceptance of defects. A use-as-is decision is typically exception-based and documented.

    Common confusion

    Use-as-is vs rework: Rework changes the item so it fully meets the original requirement. Use-as-is accepts the item without making that change.

    Use-as-is vs repair: Repair changes the item so it becomes acceptable for use, but not necessarily fully conforming to the original specification. Use-as-is involves no physical correction.

    Use-as-is vs scrap: Scrap removes the item from intended use. Use-as-is keeps it in use.

    Use-as-is vs deviation or concession: A deviation or concession is commonly the authorization mechanism or record; use-as-is is the disposition outcome.

    How it shows up in systems

    In MES, QMS, ERP, or integrated NCR workflows, use-as-is may be stored as a disposition code tied to the affected serial number, lot, batch, work order, or material record. Related data can include review notes, approval history, attachments, traceability links, and any downstream restrictions or customer communication requirements.

  • Production Confirmation

    Production confirmation is the recorded update that a production order, work order, or routing operation has been performed. It commonly captures what was completed, when it was completed, who performed it, and the quantities produced, scrapped, or reworked.

    In manufacturing systems, production confirmation is used to close the loop between planned work and actual shop-floor execution. It may be entered in an MES, ERP, digital traveler, or operator interface, and can update order status, labor time, machine time, inventory consumption, produced quantities, and traceability records.

    The exact data included depends on the process and system design. A confirmation may apply to a full production order, a single operation, a batch step, or a serialized unit. In regulated or quality-sensitive environments, it is often linked to operator signoffs, inspection results, material lots, equipment used, and timestamps.

    Production confirmation should not be confused with a customer order confirmation or sales order acknowledgment. In this context, it refers to confirmation of manufacturing execution, not confirmation that a customer order has been accepted.

  • Operational layer

    The operational layer commonly refers to the part of an industrial or manufacturing environment where production work is executed, monitored, coordinated, and recorded. It sits between high-level business planning and the physical process or equipment, translating production intent into day-to-day operational activity.

    In practice, the operational layer often includes manufacturing execution, shop floor coordination, work instructions, quality checks, scheduling detail, data collection, and traceability functions. It is where operators, supervisors, and plant systems interact with work orders, materials, equipment status, process data, and production records.

    It does not usually mean the physical device layer itself, such as sensors, PLCs, drives, or machines, and it does not usually mean the enterprise planning layer, such as long-range financial planning or corporate ERP processes. Instead, it commonly refers to the execution and control context that connects those layers.

    How the term is used in manufacturing systems

    In manufacturing and regulated operations, the operational layer is often associated with systems such as MES, production tracking tools, electronic batch or device history records, digital work instruction platforms, quality data collection, and related integration services. This layer is where planned work becomes actual work, and where operational events are captured as records.

    • Receiving production orders from enterprise systems
    • Dispatching or sequencing work on the shop floor
    • Managing operator tasks and work instructions
    • Collecting process, material, and labor data
    • Recording inspections, nonconformances, and traceability events
    • Exchanging status information with equipment and business systems

    In ISA-95 style discussions, this idea is broadly aligned with manufacturing operations management functions between enterprise planning and direct control, although organizations may use different layer names.

    Common confusion

    Operational layer is often confused with OT, control layer, or application layer.

    • OT is broader and can include control systems, networks, and devices used to operate industrial processes.
    • Control layer usually refers more narrowly to automation and real-time control components such as PLC, SCADA, or DCS functions.
    • Application layer is an IT architecture term and may refer to software structure rather than a manufacturing operating level.

    Because naming varies by vendor and architecture model, the term is best understood by its role: the layer that manages production execution and operational records.

  • Nonconforming Material (NCM)

    Nonconforming Material (NCM) commonly refers to raw material, components, subassemblies, or finished goods that do not meet one or more specified requirements. Those requirements may come from drawings, specifications, purchase requirements, process criteria, inspection results, labeling rules, or approved manufacturing instructions.

    NCM is a status or condition of material, not a root cause and not a disposition by itself. Once identified, the material is typically controlled so it is not used, shipped, or mixed with acceptable stock until an authorized review determines what happens next.

    What it includes

    • Incoming material that fails receiving inspection
    • Work-in-process that does not meet dimensional, visual, functional, or documentation requirements
    • Finished product found out of specification before release or after internal review
    • Material with incorrect identification, lot traceability, revision status, or labeling when those are required attributes

    What it does not mean

    NCM does not automatically mean scrap. Nonconforming material may be reworked, repaired where allowed, used under an approved deviation or concession where applicable, returned to supplier, or scrapped, depending on the defined review and disposition process. It also does not mean every production issue is a material issue. Equipment faults, documentation errors, and process deviations may create nonconforming output, but they are not themselves material.

    How it appears in operations and systems

    In manufacturing workflows, NCM is often identified during receiving, in-process inspection, final inspection, testing, or stockroom review. In MES, ERP, or QMS environments, it is commonly linked to a hold status, quarantine location, nonconformance record, lot or serial traceability, and a disposition workflow. The objective of those controls is to maintain visibility and prevent unintended use while the issue is being evaluated.

    Example: a batch of machined parts that fails a diameter tolerance check would be treated as nonconforming material until the parts are reviewed and dispositioned.

    Common confusion

    Nonconforming Material (NCM) is often confused with nonconformance or NCR. NCM refers to the affected material itself. A nonconformance is the condition or event in which a requirement is not met. An NCR, if used by the organization, is the record used to document and manage that condition.

    It may also be confused with scrap. Scrap is only one possible final disposition for NCM, not a synonym for it.

  • Back-testing

    Back-testing is the evaluation of a model, decision rule, forecast method, or detection logic against historical data to estimate how it would have performed if used in the past. In industrial and manufacturing settings, it commonly refers to testing analytics, alert thresholds, predictive rules, or planning logic on prior production, quality, maintenance, or supply chain data.

    It is a retrospective method. It uses existing records rather than live operation. Because of that, back-testing can help assess whether a rule appears stable, sensitive, or overly noisy before it is used in production workflows. It does not prove future performance, and it is not the same as real-time validation in current operations.

    Where it appears in manufacturing systems

    Back-testing may be used in systems and workflows such as:

    • quality analytics, for example testing whether a signal would have detected past drift or nonconformance earlier

    • maintenance analytics, for example checking whether a predictive rule would have flagged equipment issues before failure events

    • planning and inventory models, for example comparing forecast logic against historical demand and supply outcomes

    • alerting and monitoring, for example tuning thresholds against prior process, machine, or historian data

    • risk scoring or exception management, for example testing whether a scoring method would have identified past high-risk lots, orders, or suppliers

    What it includes and excludes

    Back-testing commonly includes historical input data, the rule or model being evaluated, and a comparison between predicted or triggered results and known outcomes. The historical data may come from MES, ERP, QMS, SCADA, historians, CMMS, or related systems.

    It does not by itself include model training, live deployment, or operational change control, although it may support those activities. It also does not guarantee that a model is suitable for current conditions if equipment, materials, routing, product mix, or business rules have changed since the historical period being tested.

    Common confusion

    Back-testing is often confused with simulation, validation, and benchmarking.

    • Back-testing uses real historical data and known outcomes.

    • Simulation uses assumed or generated scenarios, which may or may not match actual past conditions.

    • Validation is broader and may include back-testing, live testing, and review of data quality and assumptions.

    • Benchmarking compares performance against a reference or peer, rather than replaying history through a model.

    In finance, back-testing is strongly associated with investment strategy evaluation. In manufacturing and industrial analytics, the term more commonly refers to replaying historical operational data to evaluate detection logic, forecasts, or decision rules.

  • Spurious correlation

    Spurious correlation commonly refers to an apparent relationship between two variables that looks statistically meaningful but does not reflect a true underlying connection. The pattern may appear in charts, reports, or analytics outputs even when one variable does not meaningfully influence the other.

    In manufacturing and industrial operations, spurious correlation can appear when teams compare process, quality, maintenance, or production data and find a pattern that is coincidental, indirect, or caused by an unobserved third factor. For example, a plant may see a correlation between operator shift and defect rate, but the real driver could be product mix, machine condition, inspection timing, or missing data.

    A spurious correlation is not the same as proven causation. It also does not automatically mean the data is wrong. It means the observed association may be misleading if used without validation, domain context, or control for confounding factors.

    How it shows up in operations and systems

    • BI dashboards showing two KPIs moving together over time

    • MES, ERP, or historian data merged without enough context about timing, routing, or lot structure

    • Quality investigations that rely on trend matching alone

    • Predictive analytics or machine learning models that select variables with statistical signal but low operational meaning

    Common causes include small sample sizes, seasonal patterns, shared time trends, poor data alignment, hidden variables, and repeated slicing of data until a pattern appears.

    Common confusion

    Spurious correlation is often confused with correlation in general. Correlation only describes that variables move together; it does not explain why. It is also different from a root cause. A root cause is a validated explanation for an observed effect, while a spurious correlation is an association that may not hold up under deeper analysis.

    It can also be confused with confounding. Confounding is one common reason a correlation becomes spurious, but the terms are not identical. Confounding refers specifically to a third factor that distorts the observed relationship.

    Why the term matters

    In regulated and quality-sensitive environments, decisions based on spurious correlation can distort investigations, escalation priorities, process adjustments, and reporting. The term is commonly used as a caution in analytics, continuous improvement, and performance monitoring to distinguish observed signal from validated operational cause.

  • ISO/IEC 27001:2022

    ISO/IEC 27001:2022 is the 2022 edition of the international standard that specifies requirements for establishing, implementing, maintaining, and continually improving an Information Security Management System (ISMS). It provides a structured framework for managing information security risks for all types of organizations, including manufacturers operating regulated production and OT/IT environments.

    The standard covers how an organization defines the scope of its ISMS, assesses information security risks, selects and applies controls, and monitors performance and improvement. It is technology neutral and can be applied to on-premises systems, cloud services, operational technology (OT), and integrated IT/OT architectures.

    Key elements

    ISO/IEC 27001:2022 commonly refers to:

    • ISMS requirements: Clauses that define management-system practices such as context, leadership, planning, support, operation, performance evaluation, and improvement.
    • Annex A reference controls: A catalog of information security controls organized into themes such as organizational, people, physical, and technological controls. These are references for risk treatment, not a mandatory checklist.
    • Risk-based approach: The requirement to identify information security risks, define risk criteria, choose treatments, and document decisions in a statement of applicability.
    • Continuous improvement: Expectations for monitoring, internal audits, management review, and corrective actions to keep the ISMS effective and up to date.

    Use in industrial and regulated manufacturing environments

    In manufacturing, ISO/IEC 27001:2022 is commonly used to structure information security around systems such as MES, ERP, historians, lab systems, and OT networks. Typical applications include:

    • Defining how access to production and quality systems is governed and logged.
    • Aligning network segregation, remote access, and patching practices for OT assets with formal risk assessments.
    • Coordinating information security with quality management, document control, and audit readiness processes.
    • Supporting supplier and customer expectations around information security governance, without implying any specific certification outcome.

    Relation to other ISO/IEC 27000-series documents

    ISO/IEC 27001:2022 sits within the broader ISO/IEC 27000 family of information security standards. For example:

    • ISO/IEC 27002 provides guidance on implementing controls conceptually aligned with the Annex A controls of ISO/IEC 27001:2022.
    • Other 27000-series documents address topics such as OT security, incident management, and sector-specific guidance.

    Organizations often use 27001 as the management-system core and reference additional 27000-series standards for more detailed practices.

    Common confusion

    • Standard vs. certification: ISO/IEC 27001:2022 is a written standard. Certification is a separate process conducted by external bodies. The term “ISO 27001” is often used loosely to mean both, which can cause misunderstanding.
    • “Four categories” of controls: Training materials sometimes group Annex A controls into a small number of categories for teaching purposes. ISO/IEC 27001:2022 itself defines its own control structure and naming; it does not formally define a “four category” model.
    • 27001 vs. 27002: ISO/IEC 27001:2022 defines ISMS requirements and references control themes. ISO/IEC 27002 provides detailed implementation guidance for controls. They are related but not interchangeable.

    Context of the 2022 edition

    The 2022 edition updates and replaces earlier editions of ISO/IEC 27001. It aligns its Annex A controls with the revised ISO/IEC 27002 structure, streamlines and renames several controls, and reflects current practices in areas such as cloud services and modern networked environments. When organizations refer to “ISO 27001” in current projects or contracts, they often mean ISO/IEC 27001:2022 unless an earlier edition is explicitly specified.