Team Leader Dashboards

Team Leader Menu

Precondition: To open Team Leader dashboards select Team Leader from the main menu

Figure 1: Team Leader dashboards

Machines Summary

Precondition: To open Machines dashboard select:

The same roles can open the mobile version (lightweight information) of machines dashboard developed for tablet devices.

To open Machines Dashboard on tablets select:

Purpose: The dashboard shows a summary and detailed information for all machines in the enterprise.

From this dashboard, users can receive the following information:

  • Total number and list of machines that are running, inactive, and not online
  • List of machines with their names, statuses and duration of time with current machine status
  • Chart with overall machine statuses during the selected time period, filtered by selected department or type.
  • Total number and detailed information about active alarms
  • Factory OEE and easily open detailed Factory OEE dashboard with OEE for each machine
  • Factory Utilization and easily open detailed Factory Utilization dashboard with utilization for each machine.
  • Total Factory Cost Deviation and easily open detailed Deviations Overview dashboard
  • List with Machine details: Status, full machine name, work order, part name, operator name, and number. Links from machine name or work order can open machine OEE and work order OEE dashboards.

Figure 2: Machines summary dashboard top

Figure 3: Machines summary dashboard bottom

Machine dashboard shows:

Machines List

On the left side is a List of all machines with their Machine name, Status, Duration of time with current status. Clicking on some machine is opened the Machine Details dashboard.

Figure 4: Machines summary dashboard machines list

Machine list could be filtered by Department, Type, and Team.

Figure 5: Machines summary dashboard filters

Running, Inactive, Not Online Machines

Panels for running, inactive and not online machines are updated according to selected time period (upper right)

The section is updated according to the selected time period (upper right)

Figure 6: Machines summary dashboard -panel with running, inactive, not online machines

Pie Chart Overall Machine statuses with duration for each status for the selected time period.

Open drop-down and select one of the predefined periods.

Figure 7: Machines summary dashboard - Overall machine statuses

On the Summary machines dashboard there is a panel with Factory KPIs:

Figure 8: Machine summary dashboard - panel with factory parameters

From this section with enterprise, parameters are possible to go to other detailed dashboards.

Active Alarms

The number of active alarms in the factory for the selected time interval.

Figure 9: Machine summary dashboard - Active alarms

From panel Active Alarms click on the upper left link Alarms to open the Alarms dashboard

Total Cost Deviations

The KPI Total Cost deviation represents the deviation between actual time and planned time for the work orders planned to end in the selected time period.

Calculation:

PartCostDeviation += Operation[i].CostDeviation

WorkOrderCostDeviation += Part[i].CostDeviation

TotalCostDeviation += WorkOrder[i].CostDeviation

Note: The result is calculated as duration, in hours. However in Grafana this value is multiplied by the “cost per hour” variable to display the KPI value as currency (NOK kr). Cost deviations can be positive or negative.

Figure 10: Machine summary dashboard - Total Cost Deviation

From panel Total Cost Deviation click on the upper left link to open the Deviations Overview dashboard

Factory OEE Total

Factory OEE is calculated as an average of machines OEE for the selected time interval.

Figure 11: Machine summary dashboard - Factory OEE

From panel Factory OEE click on the upper left link to open the Factory OEE dashboard

Factory Utilization Total

Factory Utilization is calculated as an average of machines utilization for the selected time period.

Figure 12: Machine summary dashboard - Factory Utilization

Click on the upper left link Factory Utilization Details to open Factory Utilization Dashboard

Work Orders OTD (On Time Delivery)

Work orders OTD is calculated as an average for the selected time period for the factory in percentage.

Figure 13: Machine summary dashboard - Work Order OTD

For details on how are calculated OTD go to the Work Order OEE dashboard

Work Order OEE

Work Order OEE is calculated as an average work order OEE for the orders active in the selected period in percentage.

Figure 14: Machine summary dashboard - Work Order OEE

For details go to the Work Order OEE dashboard

Machines List Details

Machine Details panel shows list of machines with their: Status, Name, WorkOrder (WO), Part name (PART), Operator name (Op Name), and Operator number (OPNr)

Clicking on the link with machine name (Name column) go to the Machine OEE Details

Clicking on the number of work orderс (WO column) go to the Work Order OEE dashboard

Figure 15: Machine summary dashboard -Machine Details

Factory Utilization

Precondition: Open Machines dashboard. From the Factory Utilization panel click on the link from the upper left corner and open the Factory Utilization dashboard

Factory Utilization (%) is calculated as an average of utilizations (%) for all machines in the factory (excluding machines with ‘No data’) divided on the number of machines.

This dashboard shows Machines Utilizations of all machines in the factory for the selected time interval.

Machine Utilization (%) is calculated per day. This is the amount of time (in hours) a machine has been in some state (turned on) divided by 24 in ‘%’. The machine is in utilization mode when has some of the running or inactive statuses.

Calculation:

FactoryTotalUtilization += Machine[i].Utilization

FactoryUtilization = FactoryTotalUtilization / number of machines (with data)

From this dashboard users can:

  • Follow and view utilization of all machines in the factory for the selected time period
  • Filtering by machine type user can compare utilizations for machines of this type
  • Filtering by department user can view and analyze the utilization of machines in different departments
  • The user can open Detailed Utilization Dashboard for the selected machine

Figure 16: Factory Utilization dashboard

There is possible to filter machines by following filters:

Figure 17: Factory Utilization dashboard - Filters

Change time period

There is a possible to open the Machine Utilization dashboard by clicking on the upper left link in the machine panel.

Figure 18: Factory Utilization dashboard - Machine Utilization

There is a possible return back to Machine Summary Dashboard by top right button

Machine Utilization

Precondition: To open the Machines Utilization dashboard select:

Machine Utilization (%) is calculated per day. This is the amount of time (in hours) a machine has been in some state (turned on) divided by 24 in ‘%’. The machine is in utilization mode when has some of the running or inactive statuses.

Running statuses: Running|ACTIVE|NORMAL|Starting|AUTO|Completing|Completed|PRODUCING| Executing|READY|Preparing|Idle|Clearing|UnHolding|UnSuspending|Resetting

Inactive statuses: MANUAL|ERROR|STOPPED|Stopping|Stopped|Aborting|Aborted|Invalid| Suspending|Suspended|Holding|Held|INTERRUPTED|FEED_HOLD|PROGRAM_STOPPED|Pause|Init

Calculation:

MachineActiveTime += (MachineTime(with running statuses) OR MachineTime(with inactive statuses))

Machine Utilization = MachineActiveTime(hours) /24 *100 (%)

Figure 19: Machine OEE dashboard - Machine Utilization

From Machine OEE Dashboard users can:

  • View the average percentage of machine utilization for the selected time interval
  • Can view and analyze machine utilization during the selected time interval

Machine Details

Precondition: Open the Machines SUMARY dashboard. Click on the selected machine from the left side list.

From a detailed machine dashboard user can:

  • View percentage of Machine OEE (%) for the last day in the selected time interval
  • Open detailed Machine OEE dashboard with the average percentage of machine OEE for the selected time interval. On detailed Machine OEE dashboard is visible also machine utilization as an average percentage for the selected time interval.
  • Machine last downtime status, statuses, tool info and details
  • Can create machine maintenance task in View MMS
  • Machine status timeline during the time in the selected time interval
  • Some specific charts related to the machine
  • Planned maintenance tasks for the machine during the next 30 days
  • Predictive Maintenance (for some machines)
  • Reports -tool report, status report, program report for the selected time interval; status summary and downtime summary for the last two weeks.

Figure 20: Machine Details dashboard for Heidenhain machines

Figure 21: Fanuc machine details dashboard - Work order

It is the current OEE of the machine (%). It is calculated per day.

Clicking on the left link Machine OEE Details is opened Machine OEE dashboard. The current OEE value can be visible if select time period ‘last 24 hours’. On the Machine OEE page, OEE of the machine is changed by changing time interval.

Figure 22: Fanuc machine details dashboard - Machine OEE

Figure 23: Fanuc machine details dashboard - Work Order Logs

Figure 24:Machine Details - Create maintenance request button

When clicking on the Maintenance button is opened form for filling in the maintenance request

Figure 25: Machine Details - Create Maintenance request for machine

User filled in Shor Description (1), Description (2), select time period for maintenance task (3), and clicking Save button (4).

When there are machine tags connected to external sensors is shown button External sensors with number of sensors connected to machine tags.

By clicking on the button External sensors user can open dashboard External sensors with loaded graphics for data from machine external sensors.

Figure 26: Machine Details - Open External sensors dashboard

Figure 27: Machine Details dashboard - Machine status timeline

Figure 28: Machine Details dashboard - Downtime chart

Figure 29: Machine Details dashboard - Reports

(1)Tool report – chart with tool used during the selected time interval (the same information as in the Tool Usage dashboard for the machine)

(2)Status report – chart with status information for the selected time interval (the same as shown in the Status dashboard for the current machine)

(3) Program pie chart report

Figure 30: Machine Status Summary

Chart shows for the last two weeks, grouped by days, the durations when the machine is with different statuses: for the example: AACTIVE=9.41h, FEED_HOLD=28min, INTERRUPTED=15s, etc.

Figure 31: Machine Downtime Summary

Chart shows for the last two weeks, grouped by days, the duration when the machine is with different downtime statuses: for the example: OK=3.55h, Unplanned=8.25h, Untagged=12.20h

Predictive Maintenance & Machine Learning

Precondition: On machine details dashboard expand the panel Machine learning metrics or Predictive Maintenance

Purpose: The charts visualize the general state of degradation of a machine, in order to track over time. The ML models as Multiclass Classification and Regression models are used.

For Multiclass classification possible classes are:

Figure 32: Machine Details dashboard - Machine learning - Error class

For regression models, the values are usually in the interval 0 to 10 weeks and they describe the time interval in which to expect the failure. Min, max, and average values are calculated.

Figure 33: Machine Details dashboard - Machine learning - Remaining Useful Life

Predictive maintenance (PM) models are used for tracking the CNC machines with sensors. Charts with data for temperatures and vibrations for spindles, cooling pumps, conveyors are used for PM.

Figure 34: Machine Details dashboard - predictive maintenance of the machine

Factory OEE

Precondition: To open Factory OEE dashboard select:

Purpose: Factory OEE dashboard shows average machines OEE for the selected time interval. Machine OEE is calculated every hour.

Figure 35: Factory OEE dashboard

From the Factory OEE dashboard users can:

  • View each machine OEE for the selected time interval
  • Filter machines and check OEE by departments or type of machines or team
  • For each machine easily can open the machine OEE details dashboard

Filtering machines in the Factory OEE is possible by:

For the selected machine is possible to open the Machine OEE dashboard

Machine OEE

Precondition: To open the Machine OEE dashboard select:

Purpose: Machine OEE dashboard shows percentages of Machine Utilization, Machine OEE, Availability, Performance, and Quality for the selected time interval. Machine parameters are calculated per day.

Machine OEE = A*P*Q

From the Machine OEE dashboard users can:

  • View the average percentage of machine utilization and detailed chart graphic for the selected time interval
  • View the average percentage of machine OEE and detailed chart graphic for the selected time interval.
  • View the average percentages and detailed chart graphics for machine Quality, Performance, Availability for the selected time interval
  • Make analysis on the machine OEE parameters (performance, availability, and quality) for a different time interval

Figure 36: Machine OEE dashboard

On the dashboard are shown the following KPIs for machine:

Machine OEE

Overall Equipment Effectiveness (OEE) is the gold standard for measuring manufacturing productivity. It identifies the percentage of manufacturing time that is truly productive. An OEE score of 100% means the manufacturer produces only Good Parts (100% Quality), as fast as possible (100% Performance), with no Stop Time (100%).

Figure 37: Calculation of OEE

Machine OEE is considered the single best metric for identifying losses, benchmarking progress, and improving the productivity of manufacturing equipment.

All calculations below will assume the following structure is in place that determines the way work is planned and reported in the manufacturing domain:

Machine Availability

Availability takes into account all events that stop planned production long enough where it makes sense to track a downtime reason. Availability is calculated as the ratio of Run Time to Planned Production Time. Availability is calculated on a daily basis (or the day until now for days that have not complete).

Planned Production Time (PPT)

For each individual machine, its planned production time is derived from the shift calendar, assigned to the machine in the administration portal. Planned production time could be defined as flexible with up to 4 shifts per day and up to 3 breaks during a shift. A calendar has individual settings for each day of the week, it is selected on machine level and could be configured to start on a specific date.

Note: It is not required that every machine has an assigned calendar. If one does not then the assumption is that it is planned to work 24/7.

Run Time is equal to Planned production time PPT, excluding Stop Time (Downtime).

Calculation steps

Machine Availability = (PPT- Downtime) / PPT * 100 (%)

Note: Availability is always in the range [0%; 100%] as all of the components are positive and downtime could not exceed planned production time.

Machine Performance

Performance calculation takes into account everything that causes the manufacturing process to run suboptimally when it is running. Then performance is calculated as the ratio between the ideal running time overall cycles and the operations running time.

Note: Performance is always in the range [0%; 100%]. In case performance is calculated to above 100%, then the ideal planned time shall be readjusted.

Ideal Running Time (Ideal Cycle Time) is subject to planning and shall be the fastest cycle time that the process could achieve under optimal circumstances. Ideal running time could be available per operation level.

IdealCycleTime = TimePerItem(from ERP)

Calculation steps

Machine Performance = (IdealTimeTotal / OperationTimeTotal) * 100;

Note: The performance calculation algorithm with the utilization of cycle time on machine compared against planned time would be much more precise. Then for each operation execution, the KPI will sum up the ideal time vs the actual time, based on the NC cycle duration.

Machine Quality

Quality takes into account manufactured parts that do not meet quality standards, including parts that need rework. Quality takes into account the first pass through the manufacturing process.

Good Parts are parts that have passed quality control inspection.

Scrap Parts (Bad Parts) are parts that have not passed quality control inspection.

Calculation Steps

Machine Quality = (MinGoodPartsTotal) / (MinGoodPartsTotal + SumScrapPartsTotal) *100

Status

Precondition: To open the Status dashboard select:

Purpose: Dashboard shows detailed machine statuses information during the selected time period, for all machines in the enterprise.

Users can receive from this dashboard the following information:

  • Information about statuses of all machines in the enterprise
  • For each machine- current status and duration of time with this status
  • For a time period, selected from predefined list view:
  • Graphic with machine statuses during the time
  • Each status is with different color, duration in hours and % of working time
  • Zoom out the statuses graphic for detailed view

Figure 37: Status dashboard

Machine list could be filtered by separate machine(s) or by Team.

Custom time range could be changed by selecting the interval from last 5, 15, 30 minutes, last 1, 3, 6, 24 hours, last days, months, and years.

Users can zoom out the selected time range.

Alarms

Preconditions: To open the Alarms dashboard select:

From the Alarms dashboard user can see:

  • Current active alarms from all machines
  • Can filter only by one machine clicking on the link with machine number
  • All messages for the current time range as list and pie chard
  • All system warnings

Figure 38: Alarms Summary dashboard - Active alarms

In the section, Active alarms from All machines are shown:

Messages for one machine can be filtered by clicking on machine link or by machine filter.

In the section All Messages (current time range) from All are shown all alarm messages sent for the selected time interval (from top right).

All messages are shown also by pie chart.

Figure 39: Alarms Summary dashboard - All messages

In the section System Warnings can be visualized active system warnings, defined in the Upkip Administration by warnings and triggered by events with severity: Alarm, Warning or Information.

Figure 40: Alarms summary dashboard - Active system warnings

Maintenance

Preconditions: To open the Maintenance dashboard select:

Purpose: Dashboard Maintenance shows summary information about maintenance orders for machines and checkpoints imported from the Maintenance Management system.

From this dashboard, users can see:

  • Total checkpoints due today expired maintenance orders and orders expiring this week
  • Planned checkpoint for different machines for today, their frequency. (Point due today)
  • For each machine – summary list of maintenance work orders with their: numbers, dates from-to, priority, status, description, responsible from the MMS system.
  • URL for opening work order in the View HTS MMS for detailed information.

Figure 41: Maintenance dashboard

The Maintenance dashboard shows aggregated maintenance information for selected machines by filters(or all machines) and panel for each machine with maintenance orders and checkpointс. Maintenance orders for machines are shown from the start date of the selected time interval (top right) and 2 year ahead.

Figure 42: Maintenance dashboard - Aggregated panel

On the top of the dashboard is shown Aggregated information about maintenance work orders for all machines in the enterprise(or filtered machines): Orders expired, Orders expiring this week, Unread actions from orders, Points done today, Points due today, Point actions generated today.

Aggregated panel with maintenance KPI graphic and work orders list for all machines in the enterprise (or filtered machines).

For each machine in the enterprise are shown:

Figure 43: Maintenance dashboard - Machine Maintenance KPIs

Figure 44: Maintenance dashboard - Maintenance orders for machine

Clicking on the URL Open in View – is opened order in the MMS with detailed information.

Filtering Maintenance dashboard

Figure 45: Maintenance dashboard - Filtering machines

Tool Usage

Preconditions: To open the Tool Usage dashboard select:

Purpose: Dashboard Tool Usage shows information for all or filtered machines how many tools have been used, hours, and periods for each tool. Information comes from the machine tags.

Using this dashboard users can filter and find information about:

  • Which machine how many tools are used, duration, and periods of each tool
  • Using tools by department
  • Summary information for tool usage
  • By default, dashboard shows tool usage for the last 30 days.

Figure 46: Tool Usage dashboard

Aggregated graphics Tool Total usage is shown on the top of dashboard

For each machine in panels are shown information about the number of tool used and duration of usage.

Figure 47: Tool Usage dashboard - Machine panel

Information can be filtered by machine, department, or team.

SPC

Preconditions: To open SPC (statistical process control) dashboard select:

Purpose: SPC dashboards show measurements of different parts from the orders on measuring stations. Upkip periodically checks and imports measurement data from the Q-DAS DB.

There are two types of measurements:

SPC Measurements

Figure 48: SPC - SPC Measurements

SPC Measurement dashboard shows data from different measurements of the parts from different measuring stations.

Data can be filtered by measuring station and/or part number.

Figure 49: SPC - filtering measurements on SPC measurements

Data are shown in a table with the following columns**:**

Clicking on the link with Last Time opens the dashboard SPC Measurement Values.

SPC Measurement Values

Purpose: SPC Measurement Values dashboard shows measurement values of the part characteristics of the selected measurement by timestamp. One measurement is identified with timestamp, ID, measuring station and part.

Figure 50: SPC - SPC Measurement values of the selected measurement

Dashboard can be filtered by ID, Measuring station and Part code.

Figure 51: SPC - filtering SPC measurement values

Data from the selected measurement are shown in a table with the following columns**:**

In the table is possible to have characteristic Visual inspection with value from operator (OK/NOTOK).

Clicking on the link with Characteristic name opens the dashboard SPC Details.

SPC Details

Purpose: SPC Details dashboard shows details about measurement of the selected characteristic.

Figure 52: SPC - SPC details

Characteristic details can be filtered by measuring station, CNC machine, part and characteristic.

Figure 53: SPC - filtering SPC details

On the top panel is shown data analysis for part and characteristic.

Figure 54: SPC details - quality, outside limits and timeline

  1. Quality - shows the percentage of values inside specification limits.
  2. Outside SPEC limits – panel shows X/Y, where X – the number of characteristics outside the specification limits, Y – total number of characteristics
  3. Outside CONTROL limits - panel shows X/Y, where X – the number of characteristics outside the control limits, Y – total number of characteristics
  4. Timeline – shows measurement value and previous values (blue color), lower and upper specification limits (red lines), lower and upper control limits (yellow lines)

The next panels:

Figure 55: SPC details - data analysis

  1. Histogram over time
  2. Trend – measurement values, area of the specification and control limits
  3. Histogram over measurement values
  4. Statistics per work order – min, max and average

Figure 56: SPC details - the number of measurement in the selected time period

The table shows the number of measurements registered in the selected time period, grouped by Characteristic. The columns are: Characteristic (name), Measuring station (number), CNC machine (machine ID), Count (characteristic measurements count).

From the next panel is possible to submit upper and lower specification and control limits for the selected characteristic.

Figure 57: SPC details - submit characteristic's limits

The next panel shows raw data from characteristic measurements.

Figure 58: SPC details - raw data from characteristic measurements

CO2 Emissions

Preconditions: To open the CO2 emissions dashboard select:

Purpose: Dashboard CO2 emissions shows machine power measured by ReMoni power sensors (M222) converted to carbon released per kWh. UK CO2(eq) emissions due to electricity generation 0.23314kg CO2e per kWh.

Calculator to convert power to CO2 - https://www.rensmart.com/Calculators/KWH-to-CO2

Figure 59: CO2 emissions dashboard

CO2e kg released = Power (kWh) * 0.23314

Machine M222 of type Nakamura NTY3-150 has connected ReMoni sensor - using tag powerMainW.

Expand the CO2 panel. For the selected time period are shown:

  1. Total of CO2e (kg) released = Total power (kWh) * 0.23314

  2. Graphic of COe (kg) per hour

Expand the panel Power. The power is measured from the machine M222 tag powerMainW.

For the selected time period are shown: 3. Total of measured machine power (kWh) by the tag powerMainW 4. Graphic Power consumption readings in (W) per datetime. Min, max, average, and current power are calculated. 5. Graphic of the Power consumption (kWh) per hour 6. Graphic of the Power consumption (kWh) per day

Expand the panel Item type.

Figure 60: CO2 emissions - Item type panel

Panel shows for the selected time period:

  1. Energy and CO2 by the Item type produced. In the table are shown: Item type, Order, Part, Power (kWh) and CO2 (kg) =Power (kW) * 0.23314. Item type is connected with order and part.
  2. Power usage readings (W) during the time logged for the work orders (date-time)

Expand the panel Status and Tool usage.

Figure 61: CO2 emissions - Status and Tool usage

In the panel Status is shown:

  1. Chart with machine statuses during the selected time interval. For each status is shown the duration of time and percentage.

In the panel Tool usage are shown:

  1. Graphic for power consumption (W) for the selected time period. Power is from ReMoni sensor connected to machine tag powerMainW.

  2. Three charts for usage of the tools – Tool1, Tool2, Tool3 for the selected time period. For each number of machine tool is shown percentage of time.

Users can select some intervals from chart (2) and the tools charts below are changed for the selected time interval.

Power KPIs

Preconditions: To open Power KPIs dashboard select:

Purpose: KPIs Dashboard shows statistics about: total power consumption and average consumption used for the production of one item; total power cost and average power cost for the production of one item. The KPIs are calculated for a specific part identified by its unique Item Code, which is internal and specific to the customer.

Average energy used for one item is the weighted power consumption for the production of an item in an order as the sum of the weighted power consumptions of each part (position). The parts are calculated as the sum of the weighted power consumptions of each operation.

Figure 62: Power KPIs dashboard

Statistics on the dashboard are filtered by Work order number and by part code.

At the top is shown Order and Part Details panel. It shows Work order number, customer, order plan start date, order actual stop date, if closed or not (Y/N), part code and name, the numbers of good quantities and scrap quantities.

Figure 63: Power KPIs - order and part details

Second panel shows Statistics on work order and part

Figure 64: KPIs dashboard - statistics on work order and part

Third panel shows Statistics across all orders for the selected part.

Figure 65: KPIs dashboard - statistics across all orders for the selected part

Average consumption per item on work order

The power consumption per part KPI represents the average power consumption used for the production of one item. The resulting value is in energy consumption (Wh). The KPI is calculated for a specific part identified by its unique Item Code, which is internal and specific to the customer.

Average energy used for one item is the weighted power consumption for the production of an item in an order as the sum of the weighted power consumptions of each part(position). The parts are calculated as the sum of the weighted power consumptions of each operation.

Calculation:

WOAveragePowerConsumptionPerItem= WOPositionsPowerConsumptionPerItem/NumberOfPositions (kWh)

Average consumption per item across all work orders

The KPI Average power consumption per item is calculated also across all work orders with the same item code.

Calculation:

AllWOAveragePowerConsumptionPerItem= AllWOPositionsPowerConsumptionPerItem/AllWONumberOfPositions (kWh)

Total Order Power Consumption

The KPI Total Order Power Consumption shows the power consumption in (kWh) for operations for all parts in the work order.

With the same steps as above sum the power consumption of all operations in all parts (positions) in the order.

Calculation:

TotalOrderPowerConsumption += PartTotalPowerConsumption[i] (kWh)

Note: Cases when the calculations may be skewed:

  • If some of the machines that are used in the order don’t have power consumption sensors – the operations and work logs on those machines will not be part of the calculations and will skew the result for the order.
  • If the work time logged for machines is incorrect the power consumption values will not be correct.
  • Across different orders the scrap quantity will affect the calculations for average power consumption (more scrap equals higher average power consumption).