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| | ==== About Datonis Manufacturing Intelligence (MInt) ==== | | ==== About Datonis Manufacturing Intelligence (MInt) ==== |
| − | Datonis Manufacturing Intelligence (MInt) is a cloud-based software which transforms the organizations (Plant) manufacturing related data from heterogeneous sources to depict a comprehensive 360-degree view of the plant. Today’s BI tools are very mature in data presentation and flexible in adaptation, but this doesn’t help those working on the shop floors that need to contextualize their analysis of data with the actions they are performing. Propagation of the information between systems and people (including shop floor operators) is the real need of the manufacturing industry. | + | Datonis Manufacturing Intelligence (MInt) is a cloud-based software which transforms the organizations (Plant) manufacturing related data from heterogeneous sources to depict a comprehensive 360-degree view of the plant. |
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| | ==== Different Aspects of MInt ==== | | ==== Different Aspects of MInt ==== |
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| | * On-Demand Monitoring: Datonis Manufacturing Intelligence has a fluid design and adapts to the target device screen, so you can monitor machines and access reports literally on the go. | | * On-Demand Monitoring: Datonis Manufacturing Intelligence has a fluid design and adapts to the target device screen, so you can monitor machines and access reports literally on the go. |
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| − | === MInt Reports & Dashboards === | + | === Basic Concepts === |
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| − | ==== Productivity Module ==== | + | ==== Key Definitions ==== |
| − | Most of the time Productivity and Operational Efficiency in the manufacturing world get misinterpreted or sometimes used synonymously. '''Productivity''' is defined as a total output per one unit of the total input. '''Operational efficiency''' is the capability of an enterprise to deliver products or services to its customers in the most cost-effective manner possible while still ensuring the high quality of its products, service, and support.
| + | KPI management first starts with understanding what to measure and then how to measure. The Datonis Manufacturing Intelligence has a well-defined measurement to monitor, analyze and optimize the defined production KPIs. |
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| − | Productivity is an important aspect of Datonis Manufacturing Intelligence. It is one of the basic variables governing economic production activities. However, at the same time as productivity is seen as one of the most vital factors affecting a manufacturing company’s competitiveness.
| + | '''1) OEE''' - Overall equipment effectiveness (OEE) is a measure of how well a manufacturing operation is utilized (facilities, time and material) compared to its full potential, during the periods when it is scheduled to run. |
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| − | Overall Equipment Effectiveness (OEE) is a benchmark and a baseline for measuring manufacturing productivity. OEE is calculated based on Availability, Performance, and Quality. Each factor represents a different perspective for how close the current manufacturing process is to Ideal Production. Datonis Manufacturing Intelligence covers the Productivity at the Department, Cell/Line and at Workcenter (Machine) level. | |
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| − | Datonis Manufacturing Intelligence portraits productivity in the following manner:
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| − | ===== Management Dashboard =====
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| − | This workspace captures the productivity elements at all the Organization level. The dashboard shows summarized insights for the key KPIs like OEE, Production Quantity, CBM Alerts and Quality Alerts. This dashboard gives a bird’s eye view to the key plant stakeholders as well as executive management.
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| − | This has the following sections:
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| − | * Cells: This shows the combined KPIs OEE, Production Quantity, CBM Alerts and Quality Alerts.
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| − | * Lines: This shows the Line-level OEE, Production Quantity, CBM Alerts and Quality Alerts KPI.
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| − | (Alerts are covered in detail in the CBM and Quality modules)
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| − | ===== Productivity Dashboard =====
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| − | This is a live dashboard which shows key productivity KPIs like OEE, Production Quantity, Stoppages, Hourly Production and Top Losses for selected Cell or Line. The data shown is live data for the ongoing shift. The user can view historical data using date and shift filter.
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| − | '''Productivity at the Cell level'''
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| − | A Cell is a logical unordered set of workcenters whereas Line is an ordered set of workcenters. When user selects the cell from the Cells/Line filter, this shows the consolidated data for all workcenters defined under the selected cell. The dashboard displays OEE, Availability, Performance, Quality at a glance.
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| − | The following are the formulae used to calculate the Key KPIs:
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| | * Overall Equipment Effectiveness (OEE) = Availability * Performance * Quality | | * Overall Equipment Effectiveness (OEE) = Availability * Performance * Quality |
| | * Availability = Operating Time / Scheduled Time | | * Availability = Operating Time / Scheduled Time |
| | * Performance = (No. of parts * Ideal cycle time ) / Operating Time | | * Performance = (No. of parts * Ideal cycle time ) / Operating Time |
| | * Quality = (No. of good parts / Total parts produced ) * 100 | | * Quality = (No. of good parts / Total parts produced ) * 100 |
| − | The dashboards also display also following set of KPIs: Capacity Utilization, Uptime, Planned Downtime and Unplanned Downtime.
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| − | The following are the formulae used to calculate the KPIs:
| + | '''2) CU''' - Capacity Utilization (CU) is the extent to which an enterprise or a nation uses its installed productive capacity. |
| − | * Effective Working Time (EWT) = Total available time - Planned maintenance
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| | * Capacity Utilisation (CU) = (EWT – Planned Shut Down Time - No Demand) / EWT | | * Capacity Utilisation (CU) = (EWT – Planned Shut Down Time - No Demand) / EWT |
| − | '''Productivity at the Line level'''
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| − | A production line is a series of process steps, where the form fit or function is changed at each step to produce a product.
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| − | When the user selects the cell from the Lines, this shows the data for the last operation defined under the selected Line. The dashboard displays OEE, Availability, Performance, Quality at a glance.
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| − | The following are the formulae used to calculate the Key KPIs:
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| − | * Overall Equipment Effectiveness (OEE) = Availability * Performance * Quality
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| − | * Availability = Operating Time / Scheduled Time
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| − | * Performance = (Actual Production/Line Speed) / Operating Time
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| − | * Quality = (No. of good parts / Total parts produced ) * 100
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| − | The dashboards also display also following set of KPIs: Capacity Utilization, Uptime, Planned Downtime and Unplanned Downtime.
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| − | The following are the formulae used to calculate the KPIs:
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| | * Effective Working Time (EWT) = Total available time - Planned maintenance | | * Effective Working Time (EWT) = Total available time - Planned maintenance |
| − | * Capacity Utilisation (CU) = (EWT – Planned Shut Down Time - No Demand) / EWT
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| − | In the dashboard, the next section explains about the Production Quality and Production Losses.
| + | '''3) EU''' - Effective Utilization = Overall equipment effectiveness (OEE) * Capacity Utilization (CU) |
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| − | '''Production Quality''' | + | '''4) Cycle Time''' - Cycle Time is the total time from the beginning to the end of your process including loading, processing and unloading. A Cycle is used to calculate throughput time and mostly used in discrete manufacturing. |
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| − | The dashboard displayed the ‘Total Production’ and shift wise bifurcation along with the number of cycles it took to produce the production quantity. The dashboard also plots a bar graph to display hourly production and cycles.
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| | * Cycle Time = Loading Time + Machine Auto Cycle + Unloading Timeline | | * Cycle Time = Loading Time + Machine Auto Cycle + Unloading Timeline |
| − | (Quality aspect is discussed in detail in the Quality Module)
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| − | '''Production Losses''' | + | '''5) Downtime''' - Total time for which machine was stopped or the product is not getting produced for a selected shift or a day |
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| − | This section of the dashboard displays the production losses i.e. unplanned downtime. Again, the cumulative losses (downtime) is displayed. This also shows ‘Major’ and ‘Minor’ stoppages, the user can set the threshold for minor stoppages.
| + | '''6) Planned Downtime''' - Downtime is caused by planned maintenance, operator leave or a holiday. |
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| − | The user can also view ‘Loss Analysis’ detailed report by clicking on the icon which leads to the report. Loss Analysis at Cell/Line and workcenter level | + | ==== MInt Hierarchy ==== |
| | + | To translate the present organization structure into an IIOT enabled formation; The Datonis MInt application has the following hierarchy. |
| | + | # Department (Plant) |
| | + | # Cell or Line (under the plant) |
| | + | # Workcenter(s) (i.e. machines under a cell or a line) |
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| − | '''Productivity at Workcenter'''
| + | === Management Dashboard === |
| | + | This workspace captures the productivity elements at all the Organization level. The dashboard shows summarized insights for the key KPIs like OEE, Production Quantity, CBM Alerts and Quality Alerts. This dashboard gives a bird’s eye view to the key plant stakeholders as well as executive management. |
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| − | This mainly depicts Total Production, Cycles, OEE, availability, performance, Quality for each workcenter in the cell in a tabular format. This also shows the Total Production, Capacity Utilization (CU), Up Time and Down Time. This also shows Uptime, Planned and Unplanned Downtime, Capacity Utilization and name of the operator operating the workcenter. | + | This has the following sections: |
| | + | * Cells: This shows the combined KPIs OEE, Production Quantity, CBM Alerts and Quality Alerts. |
| | + | * Lines: This shows the Line-level OEE, Production Quantity, CBM Alerts and Quality Alerts. |
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| − | By clicking a hyperlink (on the name of the workcenter) user can open a ‘Workcenter Productivity Dashboard’ where the user can see the same KPIs for the selected workcenter.
| + | === Productivity === |
| | + | Productivity is an important aspect of Datonis Manufacturing Intelligence. It is one of the basic variables governing economic production activities. However, at the same time as productivity is seen as one of the most vital factors affecting a manufacturing company’s competitiveness. |
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| − | '''Demo Video''': https://drive.google.com/file/d/13aebJxH9Q5u72VrUW6romwsLFwMR_tDZ/view?usp=sharing
| + | Datonis Manufacturing Intelligence portraits productivity in the following manner: |
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| − | ===== Productivity Analysis for Cell / Line =====
| + | '''Productivity- User Actions''': |
| − | The Productivity Analysis report plots the key KPIs in the form of a trend. For the Cell/Line selected this shows all the indicators covering the performance measures of the Cell or line. A provision to download the data in CSV format for further statistical analysis has been given.
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| − | It shows a trend for OEE, Availability, Performance and Quality. Next to the trend chart, it also displays the KPIs in bar graph split by shift. This also covers the other productivity-related elements like Total Production, Total Down Time, and Capacity Utilization. The workcenters section shows workcenter level breakdown of above KPIs in table-format view. The user can sort on the KPI columns to represent the data in a desirable format.
| + | The bookings are added under the Actions menu. The user can perform the following bookings under the productivity module: |
| | + | * Downtime Booking |
| | + | * Production Booking |
| | + | * Book Performance Loss |
| | + | '''[[Productivity User Actions|Learn more about Productivity user actions]]''' |
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| − | A further drill-down report ‘Workcenter Trend Report’ is also available on click on the workcenter name, which is explained in the next section.
| + | '''Productivity Reports''': There are different reports covered under this: |
| | + | * Productivity Dashboard |
| | + | * Productivity Analysis |
| | + | * Production Timeline |
| | + | * Downtime Analysis |
| | + | '''[[Productivity Reports New|Learn more about Productivity reports]]''' |
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| − | '''Demo Video''':
| + | === CBM === |
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| − | ===== Productivity Analysis for Workcenter ===== | |
| − | Workcenter Analysis captures productivity elements at the workcenter. This is same as the report covered in the above section. The report displays a trend for the period of the last 30 days for the selected workcenter. The report illustrates Key KPIs like OEE, Availability, Performance and Quality trend along with the shift level split. This too covers the other productivity-related elements like Total Production, Total Down Time, and Capacity Utilization for the selected workcenter.
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| − | '''Demo Video''':
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| − | ===== Production Timeline View =====
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| − | This dashboard shows the production timeline (Gantt Chart) since the beginning of the current shift. By default, displays the current day and current shift. The data for historical dates can also be rendered. The report shows the current running status of the workcenter with statistics like produced quantity, uptime and downtime. Production Quantity is parts produced in the shift. Uptime is a total time of all productive slots (Green Slots) in the shift, Downtime comprises of planned as well as unplanned downtime.
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| − | '''Key Slots''': Productive Slots (Green Slots), Unplanned Downtime Slots (Red Slots) and Planned Downtime Slots (Yellow Slots)
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| − | A hyperlink is provided for each workcenter to drill down into a workcenter specific productivity dashboard.
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| − | '''Demo Video''':
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| − | ===== Loss Analysis =====
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| − | This report is currently under enhancement.
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| − | ===== Workcenter Loss Analysis =====
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| − | This report is currently under enhancement.
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| − | ==== Condition Based Monitoring Module ====
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| | Condition Based Monitoring (CBM) plays a crucial role in preventive maintenance. Condition Based Monitoring is the process of monitoring a parameter of condition in work center (vibration, temperature etc.), in order to identify a significant change which is indicative of a developing fault. Condition Based Monitoring has a unique benefit in that conditions that would shorten normal lifespan can be addressed before they develop into a major failure. Datonis Manufacturing Intelligence has a separate workspace for Condition Based Monitoring (CBM). | | Condition Based Monitoring (CBM) plays a crucial role in preventive maintenance. Condition Based Monitoring is the process of monitoring a parameter of condition in work center (vibration, temperature etc.), in order to identify a significant change which is indicative of a developing fault. Condition Based Monitoring has a unique benefit in that conditions that would shorten normal lifespan can be addressed before they develop into a major failure. Datonis Manufacturing Intelligence has a separate workspace for Condition Based Monitoring (CBM). |
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| − | Although there are few master data configuration related changes for CBM module. Those have been covered in the MInt Configuration Section.
| + | '''CBM- User Actions''': |
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| − | ===== CBM Dashboard =====
| + | '''[[CBM User Actions|Learn more about Machin maintenance]]''' |
| − | This is a Cell/Line level report which displays a holistic view of the defined Condition Based Monitoring (CBM) parameters for the select Cell/Line. The Report displays the data for a single day with the shift level drill-down option.
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| − | The report displays a consolidated number of points out of the limits for Critical Alerts and Warning Alerts, this also plots the machine wise bar graph for the for Critical Alerts and Warning Alerts for each workcenter. The user can click on the bar-graph to navigate to the Workcenter CBM Dashboard report.
| + | '''CBM- Reports''': |
| | + | * CBM Dashboard at Cell/Line |
| | + | * CBM Dashboard at workcenter |
| | + | * MTBF and MTTR Reports at Cell/Line |
| | + | * MTBF and MTTR Reports at workcenter |
| | + | '''[[CBM Reports|Learn more about Condition based monitoring reports]]''' |
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| − | The workspace also displays ‘Machine Overdue’ alert with a hyperlink for a drill-down view and cumulative major and minor stoppages for the selected Cell/Line for the selected day and shift.
| + | === Quality === |
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| − | The send half of the report displays the above KPI information i.e. Critical and Warning alerts, Major and Minor Stoppages and Maintenance overdue (Yes/No) in a tabular format. The user can click on the workcenter name to view the Workcenter CBM Dashboard report.
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| − | ====== Workcenter Maintenance ======
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| − | The user can click on the ‘Maintenance Overdue’ tile to access this report. The repost displays the following information for the selected Cell/Line:
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| − | * Workcenter Name
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| − | * Health Remaining
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| − | * Last Maintenance Time
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| − | * Duration
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| − | * Likely Maintenance Due Time
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| − | The Report also provides two action buttons:
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| − | * Add Maintenance Record: The user can add a maintenance history for a workcenter. The form allows user to add Maintenance Start Time and End Time, Type (Planned or Unplanned), Maintenance Details and Maintenance Done By (which name of the person who has done the maintenance work.)
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| − | * Maintenance Record History: It displays the past records for the selected workcenter like Start Time, End Time, Duration (Hours), Threshold, Maintenance Details and Person who had done the maintenance.
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| − | '''Demo Video''':
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| − | ===== Workcenter CBM Dashboard =====
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| − | This report can be viewed by clicking on any workcenter from the CBM Dashboard. The report depicts a heatmap showing hourly summarized condition monitoring insights like critical and warning alerts, for the selected workcenter and parameters. The user can select multiple parameters. It also provides a raw data plot of the configured parameters with statistics like Min, Max, Avg, Std Dev, PoL, Dev from Target, Cp and CpK.
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| − | Detailed statistical tools (P, X, R, S, I-MR Chart) to analyse the variations in the parameters can be accessed by clicking on the CBM parameter name.
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| − | ===== Parameter SPC Report =====
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| − | As described in the above report, the Parameter SPC report can be accessed by clicking on any workcenter parameter from the Workcenter CBM Dashboard. This report displays a run chart of the configured CBM parameters along with the SPC charts for the selected machine, Parameter, Date and Shift.
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| − | The first chart is a raw data run chart with user-defined control and warning limits. Along with the run chart some statistics of the data are shown alongside the chart. These include Min, Mean, Max, Std Dev, Dev from Target, Cp and CpK.
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| − | The next run charts are the SPC charts which include P chart, X chart, S chart, R chart, Individuals Chart and Moving Range chart.
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| − | '''Demo Video''':
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| − | ===== MTBF and MTTR Report =====
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| − | Mean time between failures (MTBF) is the predicted elapsed time between inherent failures of a mechanical or electronic system, during normal system operation.
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| − | * Mean Time Between Failure (MTBF): Total Down Time / Count of Down Time(s)
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| − | Mean time to recovery (MTTR) is the average time that a device will take to recover from any failure.
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| − | The first workspace displays overall MTBF/MTTR by reasons with an aggregated value for the selected Cell/Line for the selected period. A filter for the category is also available if the user wished to focus on a specific reason.
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| − | The subsequent report displays a line graph for each reason by plotting MTBF and MTTR values against the date on the x-axis.
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| − | ===== Workcenter MTBF and MTTR Report =====
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| − | The reports display workcenter specific MTBF and MTTR. A filter for the category is also available if the user wished to focus on a specific reason.
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| − | The subsequent report displays a line graph for each reason by plotting MTBF and MTTR values against the date on the x-axis.
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| − | '''Demo Video''':
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| − | ==== Quality Module ====
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| | Quality is another important aspect of production and so as of Datonis Manufacturing Intelligence. The effects of quality bottlenecks can be reflected across the entire line or cell. The continuous efforts to deliver quality products while balancing optimal throughput is an important measure to help manage manufacturing processes. Datonis Manufacturing Intelligence tries to cover the quality aspects of it from the rejection bookings and its impact can be also represented in the application in its reports. | | Quality is another important aspect of production and so as of Datonis Manufacturing Intelligence. The effects of quality bottlenecks can be reflected across the entire line or cell. The continuous efforts to deliver quality products while balancing optimal throughput is an important measure to help manage manufacturing processes. Datonis Manufacturing Intelligence tries to cover the quality aspects of it from the rejection bookings and its impact can be also represented in the application in its reports. |
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| − | ===== Quality Dashboard =====
| + | '''[[Quality Reports|Learn more about Quality reports]]''' |
| − | This is a Cell/Line level dashboard which displays the live data for the current day across all shifts. The very first workspace displays overall part quality and it shows per part rejection quantity along with the quality percentage.
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| − | * Quality = (No. of good parts / Total parts produced ) * 100
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| − | It also summarizes other important quality metrics like process alerts which display the number of points out of the limits for critical and warning limits, Part Characteristics alerts again this shows the number of points out of the limit for critical and warning alerts.
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| − | For the process alert, it refers to the defined ‘Warning and Specification Limits’ set in the part quality while defining the part.
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| − | The last workspace displays the above-mentioned key quality parameters in the tabular format for each part. This table is informative to get the insight of how many rejections are been booked in the overall production of each part. This table covers the number of alerts (critical and warning) for the process, part characteristics and QC plan adherence respectively. Finally, it also displays the overall quality percentage for the part. Again, the quality is measured as Quality = (No. of good parts / Total parts produced ) * 100
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| − | ===== Part Quality Dashboard =====
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| − | The part quality dashboard has been allocated thee separate workspaces: Summary View, Process View and Part Characteristics View respectively.
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| − | * '''Summary View''':
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| − | <u>Quality by Operation</u>: This is the graphical representation in the bar chart showing the rejected quantity for each operation performed for that Part.
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| − | <u>Quality by Rejection Code</u>: This chart shows how much is the rejection happened by each of the rejection code with which the part is been rejected in the Quality inspection. This is a very important view to find out what are the main reasons in the Part Quality measurements because of which a particular part is been rejected. When the quality inspection person has done a quality check, the batch/lot of the part produced can be selected to find out the rejection.
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| − | <u>Rejection by Workcenter</u>: This chart shows how much is the rejection happened by each of the
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| − | * '''Process View''': The process view sections show the quality performance of the overall process when a part was being made.
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| − | The workspace shows the number of parameters monitored along with critical and warning alerts i.e. point out of the limits based on the part quality for the selected part, timeframe, and shift.
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| − | <u>Alerts by Operation</u>: For the selected part, timeframe, and shift; This is the graphical representation in the bar chart shows the critical and warning alerts for the entire selected duration each operation performed for that Part.
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| − | <u>Alerts by Workcenter</u>: The bar graph displays critical and warning alert raised for each workcenter where the selected part was made in the selected duration.
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| − | <u>Alerts by Shift</u>: The chart shows shift wise critical and warning alert raised for the part in question for the entire selected duration. If ‘All Shifts’ is selected in the filter, then it will display for all configured shifts for that Cell/Line.
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| − | * '''Part Characteristics View''': This section of the dashboard deals with the ‘Part Characteristics’ properties which are defined for the part. The page layout inducing the look and feel plus charts are exactly similar to the ‘Process View’. The only change is it displays quality metric with respect to ‘Part Characteristics’ parameters defined for the part.
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| − | The workspace shows the number of parameters monitored along with critical and warning alerts i.e. point out of the limits based on the part quality for the selected part, timeframe, and shift.
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| − | <u>Alerts by Operation</u>: For the selected part, timeframe, and shift; This is the graphical representation in the bar chart shows the critical and warning alerts for the entire selected duration each operation performed for that Part.
| + | Datonis Manufacturing Intelligence also has a provision to record quality samples and maintain a digital trace using Inspection Policy module. |
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| − | <u>Alerts by Workcenter</u>: The bar graph displays critical and warning alert raised for each workcenter where the selected part was made in the selected duration.
| + | '''[[Inspection Policy|Learn more about Inspection Policy]]''' |
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| − | <u>Alerts by Shift</u>: The chart shows shift wise critical and warning alert raised for the part in question for the entire selected duration. If ‘All Shifts’ is selected in the filter, then it will display for all configured shifts for that Cell/Line.
| + | === Energy === |
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| − | '''Demo Video''':
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| − | ===== Quality Parameter Analysis =====
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| − | The ‘Quality Heatmap’ workspace displays a heatmap showing the list of the quality parameter with an hourly aggregated point out of the limits with colour coding. Each hour window is represented as a cell for every parameter and colour of the cells are based on the type alert generated: Green for no alert, Yellow for Warnings and Red for Critical alerts. The number in the cell represents no of points went out of the limits.
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| − | The next workspace provides a raw data plot of the configured parameters with statistics showing Min, Max, Avg, Std Dev, PoL, Dev from Target, Cp and CpK. A hyperlink is provided (on the parameter name) to get statistical tools (P, X, R, S, I-MR Chart) to analyse the variations in the parameters.
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| − | ====== Quality Parameter SPC Report ======
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| − | As described in the above report, the Parameter SPC report can be accessed by clicking on any workcenter parameter from the Quality Parameter Analysis report. This report displays a run chart of the configured Process parameters along with the SPC charts for the selected machine, Parameter, Date and Shift.
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| − | The first chart is a raw data run chart with user defined control and warning limits. Along with the run chart, some statistics of the data are shown alongside the chart. These include Min, Mean, Max, Std Dev, Dev from Target, Cp and CpK.
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| − | The next run charts are the SPC charts which include P chart, X chart, S chart, R chart, Individuals Chart and Moving Range chart.
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| − | ==== Energy Module ====
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| | Datonis Manufacturing Intelligence also covers the Energy workspace with two out of the box utilities i.e. electricity and Compressed Air. If a plant uses more utilities, there is a provision to add them. This gives an overview of the Utilities configured in the Plant. | | Datonis Manufacturing Intelligence also covers the Energy workspace with two out of the box utilities i.e. electricity and Compressed Air. If a plant uses more utilities, there is a provision to add them. This gives an overview of the Utilities configured in the Plant. |
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| − | ===== Energy Dashboard =====
| + | The following reports are covered under energy workspace: |
| − | This is the Cell/Line level utilities consumption view. This dashboard shows summarized energy and utilities consumption metrics like Kilowatt Hour consumption (Kwh) for Electricity and the amount of compressed air for Compress Air. It displays the total consumption and hourly consumption since the beginning of the shift. This report also shows the workcenter summary which is nothing but the utilization of these metrics in each workcenter.
| + | * Energy Dashboard |
| | + | * Energy Analysis |
| | + | '''[[Energy Reports|Learn more about Energy Reports]]''' |
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| − | ===== Workcenter Energy Dashboard ===== | + | === Workorder === |
| − | On the cell/line level Energy dashboard, the hyperlinks are provided to get detailed workcenter level insights into consumption patterns. This workcenter dashboard shows energy and utilities consumption metrics like total consumption and hourly consumption since the beginning of the shift.
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| − | ===== Energy Analysis =====
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| − | This dashboard shows consumption trends for the selected cell/line over the selected period. The total consumption across different energy and utilities metrics are displayed. Shift level bifurcation is also provided for shift level consumption analysis. Workcenter level consumption data is displayed in a tabular format which can be sorted across different parameters. The workcenter consumption details can be accessed on hyperlinks.
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| − | ===== Workcenter Energy Analysis =====
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| − | This report shows consumption trends for the chosen workcenter over the selected period. The total consumption across different energy and utilities metrics along with average consumption across shifts is also displayed.
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| − | '''Demo Video''':
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| − | ==== Work order Module ====
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| | The Work order is another workspace in Datonis Manufacturing Intelligence. This captures the overall production happened for a Part for the planned work order. This provides a detailed view of the work order progress. Datonis Manufacturing Intelligence also allows creating the Workorder for a Part. Work order also maintains its life cycle in terms of when it is planned vs when it is completed and other aspects of it. | | The Work order is another workspace in Datonis Manufacturing Intelligence. This captures the overall production happened for a Part for the planned work order. This provides a detailed view of the work order progress. Datonis Manufacturing Intelligence also allows creating the Workorder for a Part. Work order also maintains its life cycle in terms of when it is planned vs when it is completed and other aspects of it. |
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| − | ===== Work orders Dashboard =====
| + | '''[[Workorders Workspace|Learn more about Workorders]]''' |
| − | The dashboard displays Planned vs Completed Quantity, this gives the pictorial view of each work order and its planned/completed count. Planned vs Competed graph represents the details of how each work order is performing. The Gantt chart representation helps to track the lagging work orders in their completion and which are on track. Work order details like Part, Planned and Actual Start Time and End Time with Planned, Completed and Rejected Quantities are displayed in a tabular format.
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| − | ===== Workorder Details =====
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| − | This report represents the progress of selected work order by showing Planned, Completed, Remaining and Rejected Quantities. It also shows Gantt chart representation to track the workorder over the execution timeline. This basically describes the deliverables planned for the given timeframe. A table ‘Workorder Analysis for operation’ displays operation performed on the workcenter, Actual Start and End, Produced Quantity and Rejected Quantity.
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| − | '''Demo Video''': | |
Datonis Manufacturing Intelligence (MInt) is a cloud-based software which transforms the organizations (Plant) manufacturing related data from heterogeneous sources to depict a comprehensive 360-degree view of the plant.
The following are Datonis Manufacturing Intelligence (MInt) key characteristics:
KPI management first starts with understanding what to measure and then how to measure. The Datonis Manufacturing Intelligence has a well-defined measurement to monitor, analyze and optimize the defined production KPIs.
To translate the present organization structure into an IIOT enabled formation; The Datonis MInt application has the following hierarchy.
This workspace captures the productivity elements at all the Organization level. The dashboard shows summarized insights for the key KPIs like OEE, Production Quantity, CBM Alerts and Quality Alerts. This dashboard gives a bird’s eye view to the key plant stakeholders as well as executive management.
Productivity is an important aspect of Datonis Manufacturing Intelligence. It is one of the basic variables governing economic production activities. However, at the same time as productivity is seen as one of the most vital factors affecting a manufacturing company’s competitiveness.
Datonis Manufacturing Intelligence portraits productivity in the following manner:
The bookings are added under the Actions menu. The user can perform the following bookings under the productivity module:
Condition Based Monitoring (CBM) plays a crucial role in preventive maintenance. Condition Based Monitoring is the process of monitoring a parameter of condition in work center (vibration, temperature etc.), in order to identify a significant change which is indicative of a developing fault. Condition Based Monitoring has a unique benefit in that conditions that would shorten normal lifespan can be addressed before they develop into a major failure. Datonis Manufacturing Intelligence has a separate workspace for Condition Based Monitoring (CBM).
Quality is another important aspect of production and so as of Datonis Manufacturing Intelligence. The effects of quality bottlenecks can be reflected across the entire line or cell. The continuous efforts to deliver quality products while balancing optimal throughput is an important measure to help manage manufacturing processes. Datonis Manufacturing Intelligence tries to cover the quality aspects of it from the rejection bookings and its impact can be also represented in the application in its reports.
Datonis Manufacturing Intelligence also has a provision to record quality samples and maintain a digital trace using Inspection Policy module.
Datonis Manufacturing Intelligence also covers the Energy workspace with two out of the box utilities i.e. electricity and Compressed Air. If a plant uses more utilities, there is a provision to add them. This gives an overview of the Utilities configured in the Plant.
The Work order is another workspace in Datonis Manufacturing Intelligence. This captures the overall production happened for a Part for the planned work order. This provides a detailed view of the work order progress. Datonis Manufacturing Intelligence also allows creating the Workorder for a Part. Work order also maintains its life cycle in terms of when it is planned vs when it is completed and other aspects of it.
