Introduction

The IBM Asset Analytics for Manufacturing Equipment in Automotive solution delivers information and insights into the functioning of robotic equipment in the automotive industry. Dashboards provide maintenance operators with visualizations that indicate the status of equipment and provide predictions about when equipment will fail.

Audience

This guide is intended for administrators and users of the Asset Analytics for Manufacturing Equipment in Automotive solution. It provides information on installation, configuration, and use of the Asset Analytics for Manufacturing Equipment in Automotive solution.

Finding information

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Forward-looking statements

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Overview

The IBM® Asset Analytics for Manufacturing Equipment in Automotive solution works with IBM Predictive Maintenance and Quality. It is designed to help the automotive industry enhance robotic equipment productivity, especially in critical manufacturing functions such as power train, body and weld, paint shop, and final assembly.

Important: Before you install the solution, IBM Predictive Maintenance and Quality 2.5.1 must be installed on your system.

The solution is designed to improve process efficiency, increase asset productivity, manage asset and quality risks, and reduce warranty or scrap cost. It helps companies in the automotive industry to improve operations in the following ways:

Enhance manufacturing productivity by using predictive analytics to maximize robotic equipment uptime.

Minimize the cost of maintenance of robotic equipment by adopting predictive maintenance.

Improve the quality of the manufactured product, which minimizes warranty service and scrap losses.

What need does the solution address?

Automotive manufacturing operations currently involve the use of robotic equipment on the shop floor to provide high precision and high yield work. This equipment is used especially for power train, body and weld, paint shop, and final assembly (transfer cells). Significant costs are associated with production continuity, manufactured product quality, and resource allocation. Although existing tools allow for sensor data collection for robotic equipment, these tools are limited to the tracking of current performance and drilling down on current failure. The unexpected failure of equipment results in significant losses due to lost productivity and scrap.

What does the solution provide?

IBM Asset Analytics for Manufacturing Equipment in Automotive provides prepackaged support for industry use cases that involve robotic assets. It includes predictive models for asset failure analysis, key performance indicators (KPIs) for asset performance, an asset health indicator, a system health indicator, and actionable inferences for reducing risk, losses, and downtime. The solution provides a stack that includes data integration services and business analytics software, providing insights and actionable recommendations in real time.

The solution provides the following features:

Visualizations to provide insight into manufacturing quality and the risk of failure for robotic equipment

Specialized predictive analytical models for robotic equipment and its operation

Dashboards to provide insights to people in a maintenance role

Easy integration and common deployment with IBM® Predictive Maintenance and Quality

Access to IBM® Predictive Maintenance and Quality tools for model, dashboard, report customization, and EAM work order creation and customization

How is the solution used by an organization?

The solution can be used by maintenance or operations organizations in the automotive industry to do the following things:

Gain situational awareness of robotic equipment

Establish a risk ranking

Predict when equipment will either fail or reach a level of poor performance that will lead to unacceptable manufactured product quality

Abililty to automatically trigger and generate maintenance recommendations

Installation and configuration

The Asset Analytics for Manufacturing Equipment in Automotive solution is for use with IBM® Predictive Maintenance and Quality.

An installation (servers and content) of IBM Predictive Maintenance and Quality 2.5.1 must be complete before the solution is installed.

Planning the installation and configuration of the solution

Prerequisites
Before you install the Asset Analytics for Manufacturing Equipment in Automotive solution, there are prerequisites that must be met.

Downloading the solution
You must download the Asset Analytics for Manufacturing Equipment in Automotive solution from IBM Passport Advantage.

Modifying the sudoers file for the user who runs the installation
To run the Asset Analytics for Manufacturing Equipment in Automotive installation, you must be either root user or have sudo permission on each node computer, and you must disable requiretty during the installation.

Computer firewall settings required for the installation
The solution installer requires bidirectional communication with each node when you install a server component or server artifact component, and your firewall can interfere with this communication.

Deploying the installation files on the nodes
You use the Solution Installer to deploy the installation files to the appropriate nodes.

Installing the database node artifact
The IBMPMQ_additional.sql file is an additional DDL to be run on top of the PMQ Data Model DDL. It is to be executed on the Database node IBMPMQ.

Installing the ESB node artifact
You must move the properties, orchestration, and solution definition files to the appropriate directories on your IBM Integration Bus node computer.

Deployment and Configuration of the SPSS Analytics Node
To prepare SPSS Collaboration and Deployment Services, you must set up links between the data in the database and the data used in the enterprise and in the application.

Onboard equipment data
Custom flows are provided with the Asset Analytics for Manufacturing Equipment in Automotive solution. You use the custom flows to onboard equipment data and to trigger training and scoring models.

Event data
Event data must also be loaded for the Asset Analytics for Manufacturing Equipment in Automotive solution.

Deploying the IBM Cognos content
For IBM Cognos Business Intelligence, you must catalog the database, create a data source connection, and then deploy the content files for the IBM Asset Analytics for Manufacturing Equipment in Automotive solution.

Planning the installation and configuration of the solution

Prepare a deployment plan to specify which part of the solution is to be deployed and on which computer node. You must ensure that no application is listening on the ports that are used during the installation of the solution.

Note: Ensure that the system ports that will be used by this solution are not used by any other application.

Parent topic: Installation and configuration

Prerequisites

Before you install the Asset Analytics for Manufacturing Equipment in Automotive solution, there are prerequisites that must be met.

The following conditions must be met before the solution can be installed:

You understand your existing environment so that you can determine where you want the various components of the application to reside.

You have a Red Hat Enterprise Linux operating system that you can install to. The Solution Installer works only on that version of Linux.

You have administration rights and the ability to copy files between computers.

IBM® Predictive Maintenance and Quality 2.5.1 is installed and configured.

Parent topic: Installation and configuration

Downloading the solution

You must download the Asset Analytics for Manufacturing Equipment in Automotive solution from IBM Passport Advantage.

Before you begin

You must have a Passport Advantage account and be entitled to the package.

About this task

Passport Advantage contains package repositories. Instead of downloading the package from Passport Advantage and creating a repository locally, you access the repository on Passport Advantage.

Procedure

Set the Passport Advantage preference to connect to Passport Advantage.

Download the tar.gz file.

Move the tar file to the Linux node from which you want to run the installation.

Uncompress the tar file.

Contents of the download package
The Asset Analytics for Manufacturing Equipment in Automotive solution package, which you download from Passport Advantage, contains several parts.

Parent topic: Installation and configuration

Contents of the download package

The Asset Analytics for Manufacturing Equipment in Automotive solution package, which you download from Passport Advantage, contains several parts.

The following parts are included in the package:

Analytics node artifacts: The IBM SPSS content is provided in a .pes file that you import into the IBM SPSS Collaboration and Deployment Services Content Repository. It consists of a training model and job, and a scoring model and job, and the decision management rules stream.

Data node artifacts: SQL files for creating the production data table in the IBMPMQ database and for importing data for those tables.

Business Intelligence (BI) node artifacts: IBM COGNOS BI dashboards, images that are used in the dashboards, a map specification, and the Framework Manager model.

ESB node artifacts: IBM Integration Bus solution bar files for custom flows to onboard data and trigger the analytics training and scoring jobs. Also included are WebSphere MQ scripts, properties, and XML files that are required by the custom flows and for IBM Predictive Maintenance and Quality core components.

Parent topic: Downloading the solution

Modifying the sudoers file for the user who runs the installation

To run the Asset Analytics for Manufacturing Equipment in Automotive installation, you must be either root user or have sudo permission on each node computer, and you must disable requiretty during the installation.

To install with sudo user permissions, you must also add the user to the sudoers file.

Procedure

Log in as root user.

Enter the following command to open the sudoers file for editing:

visudo -f /etc/sudoers

Locate the following line:

                        Defaults requiretty

Press the I key to insert text.

Type a number sign ( #) in front of Defaults requiretty to comment out the line. For example, the line will appears as #Defaults requiretty

If you run the installer as a user with sudo user permissions, go to the end of the file, and add the following line for your user:

                           username ALL=(ALL) NOPASSWD: ALL

Press the Esc key, and enter :wq to save and close the file.

Repeat these steps on each computer on which you install a Asset Analytics for Manufacturing Equipment in Automotive node.

Parent topic: Installation and configuration

Computer firewall settings required for the installation

The solution installer requires bidirectional communication with each node when you install a server component or server artifact component, and your firewall can interfere with this communication.

To ensure bidirectional communication, you must configure your firewall settings for the installation. Alternatively, you can temporarily disable your firewall during the installation.

A script is provided to open all necessary ports on the installation node. You can either use the firewall.sh script, open the ports manually, or disable the firewall settings.

In addition to opening ports on the installation node computer, you must open some ports on each computer to which content from the solution will be copied.

Configuring your firewall settings on the installation node computer by using the Firewall script
You can run the firewall.sh script to open the ports on the installation node.

Manually configuring firewall settings on the installation node
If you prefer not to disable your firewall settings or use the firewall.sh script, you can manually configure your firewall settings on the installation node.

Configuring firewall settings on other computers that will contain content from the solution
On all node computers to which content from the solution will be copied, the ports 443, 9683, and 8080 must be opened for the installation process.

Disabling firewall settings during installation (optional)
If you choose to temporarily disable your computer's firewall during the installation of the IBM Asset Analytics for Manufacturing Equipment in Automotive solution, ensure that you enable the firewall on each node after the installation is complete.

Parent topic: Installation and configuration

Configuring your firewall settings on the installation node computer by using the Firewall script

You can run the firewall.sh script to open the ports on the installation node.

About this task

The firewall.sh script opens the following ports on the solution installer node:

8080 incoming

443 incoming

9683 incoming

22 outgoing

Procedure

As the root user or as a user with sudo permissions, log on to the computer that contains the solution installer node.

Back up your existing firewall settings by typing the following command: /etc/init.d/iptables save.

Run the firewall.sh script.

Parent topic: Computer firewall settings required for the installation

Manually configuring firewall settings on the installation node

If you prefer not to disable your firewall settings or use the firewall.sh script, you can manually configure your firewall settings on the installation node.

Procedure

As the root user or as a user with sudo permissions, log on to the computer that contains the solution installer node .

Back up your existing firewall settings by typing the following command: . /etc/init.d/iptables save

On the computer that contains the solution installer node, add rules for the ports that are required by the installer by typing the following commands:

                           iptables -I INPUT -p tcp --dport 8080 -j ACCEPT
                              iptables -I OUTPUT -p tcp --sport 8080 -m state --state
                              RELATED,ESTABLISHED -j ACCEPT

                           iptables -I INPUT -p tcp --dport 443 -j ACCEPT
                              iptables -I OUTPUT -p tcp --sport 443 -m state --state
                              RELATED,ESTABLISHED -j ACCEPT

                           iptables -I INPUT -p tcp --dport 9683 -j ACCEPT
                              iptables -I OUTPUT -p tcp --sport 9683 -m state --state
                              RELATED,ESTABLISHED -j ACCEPT

                           iptables -I OUTPUT -p tcp --dport 22 -j ACCEPT
                              iptables -I INPUT -p tcp --sport 22 -m state --state
                              RELATED,ESTABLISHED -j ACCEPT

Parent topic: Computer firewall settings required for the installation

Configuring firewall settings on other computers that will contain content from the solution

On all node computers to which content from the solution will be copied, the ports 443, 9683, and 8080 must be opened for the installation process.

Procedure

On each of the computers to which content for the solution will be copied, add rules for the ports that are required by the installer by typing the following commands:

                           iptables -I OUTPUT -p tcp --dport 443 -j ACCEPT
                              iptables -I INPUT -p tcp --sport 443 -m state --state RELATED,ESTABLISHED -j ACCEPT

                           iptables -I OUTPUT -p tcp --dport 9683 -j ACCEPT
                              iptables -I INPUT -p tcp --sport 9683 -m state --state RELATED,ESTABLISHED -j ACCEPT

                           iptables -I OUTPUT -p tcp --dport 8080 -j ACCEPT
                              iptables -I INPUT -p tcp --sport 8080 -m state --state RELATED,ESTABLISHED -j ACCEPT

Type the following command to save your firewall settings:

/etc/init.d/iptables save

Type the following command to restart your firewall:

/etc/init.d/iptables restart

Verify that your changes are applied by using the following command:

iptables -L

The added port appears in the list.

Repeat these steps on each computer on which you will install an IBM Asset Analytics for Manufacturing Equipment in Automotive node.

Parent topic: Computer firewall settings required for the installation

Disabling firewall settings during installation (optional)

If you choose to temporarily disable your computer's firewall during the installation of the IBM Asset Analytics for Manufacturing Equipment in Automotive solution, ensure that you enable the firewall on each node after the installation is complete.

About this task

Important: If you disable your computer's firewall during the installation, you must still ensure that the required ports are opened on each node computer when you restart your firewall.

Procedure

Log on to the computer as the root user or as a user with sudo permissions.

Type the following command:

/etc/init.d/iptables stop

/etc/init.d/iptables save

Repeat these steps on each computer on which you install a node and on the server from which you are running the installation.

What to do next

After the installation is complete, on each node, type /etc/init.d/iptables start to restart your firewall.

Parent topic: Computer firewall settings required for the installation

Deploying the installation files on the nodes

You use the Solution Installer to deploy the installation files to the appropriate nodes.

Before you begin

Ensure that you know the following information for each of the nodes in your solution:

Host name or IP address

Password of the root user ID or a user ID and password that has sudo permissions

About this task

In this task, you create an installation configuration of your solution by dragging nodes onto a canvas, adding components to the nodes, and defining properties for the components.

Procedure

Log on to the computer where you downloaded the solution package.

Decompress the solution package.

Go to the solution installer directory. For example:

                        /<...>/CN82XEN/SolutionInstaller/

Enter the following command:

                        ./firewall.sh

The ports that are used to transfer files to the nodes are opened on the server.

Enter the following command:

                        ./setup.sh
                           username
                           first name
                           last name
                           email

The web server is started and the URL for the Solution Installer is displayed in the command line.

Start the Solution Installer by pasting the URL into a web browser.

https://<Hostname>:8080/UI/index.html

Read the license agreement and click Accept.

Click New Configuration and then click OK.

Define the Business Intelligence node:

Under Mandatory Content List, drag a Node onto the canvas.

Under Property Editor, enter values for the Business Intelligence node.

Drag Cognos BI Content onto the node. Do not change the values under Property Editor.

Drag Cognos BI Report Images onto Cognos BI Content . Do not change the values under Property Editor.

Define the DBNode and drag Database Content onto DBNode. Do not change the values under Property Editor .

Define the IBM Integration Bus node:

Under Mandatory Content List, drag a Node onto the canvas.

Under Property Editor, enter values for the IBM Integration Bus node.

Drag IBM Integration Bus Content onto the node. Do not change the values under Property Editor.

Parent topic: Installation and configuration

Installing the database node artifact

The IBMPMQ_additional.sql file is an additional DDL to be run on top of the PMQ Data Model DDL. It is to be executed on the Database node IBMPMQ.

Parent topic: Installation and configuration

Installing the ESB node artifact

You must move the properties, orchestration, and solution definition files to the appropriate directories on your IBM Integration Bus node computer.

Procedure

Log in to the Integration Bus node computer as the mqm user.

The user must be the mqm user or a member of the mqm group. If you copy the files as another user, they might not be processed by the Integration Bus node components.

Go to the directory where you installed the solution content files.

The default path where the files are deployed is /opt/IBM/IS_ManEquipAuto_AssetAnalytics_1.0/ .

Copy the PMQ_solution_definition.xml files from the Scripts directory ( /opt/IBM/IS_ManEquipAuto_AssetAnalytics_1.0/Scripts) to the /var/mqsi/shared-classes directory.

Copy the PMQ_orchestration_definition_batch.xml file from the Scripts directory ( /opt/IBM/IS_ManEquipAuto_AssetAnalytics_1.0/Scripts) to the /var/PMQ/MQSIFileInput/properties directory on the IBM Integration Bus node.

Copy the PMQ_orchestration_definition_mea.xml file from the Scripts directory ( /opt/IBM/IS_ManEquipAuto_AssetAnalytics_1.0/Scripts) to the /var/mqsi/shared-classes/orchestrations directory on the IBM Integration Bus Node.

Updating the orchestration files
You must update the orchestration files to include the server name and port number for your IBM SPSS Collaboration and Deployment Services server that is running on your IBM Predictive Maintenance and Quality Analytics node.

Creating queues

Deploying BAR files
Bar files must be deployed to the broker pmqbroker with the execution group pmqgroup1.

Source code files
The MEAIntegration_PI.zip file and PMQEventDataLoad_PI.zip file provide the source code for the IBM Integration Bus flow and code.

Parent topic: Installation and configuration

Updating the orchestration files

You must update the orchestration files to include the server name and port number for your IBM SPSS Collaboration and Deployment Services server that is running on your IBM Predictive Maintenance and Quality Analytics node.

Procedure

On the Integration Bus node computer, go to the /var/PMQ/MQSIFileInput/ properties, and open the PMQ_orchestration_definition_batch.xml file in a text editor.

To configure and schedule the SPSS training Job invocation, in the <MEATraining> identifier section, In the <webservice> section, change the <url> value to the server name and port number for your IBM SPSS Collaboration and Deployment Services server.

In the MEA identifier section, do the following steps for configuring the SPSS analytics Job invocation:

In the <webservice> section, change the <url> value to the server name and port number for your IBM SPSS Collaboration and Deployment Services server.

In the <scheduler> section, Update the scheduled_time and duration_in_days.

Save and close the file.

Parent topic: Installing the ESB node artifact

Creating queues

Procedure

Copy the IBMPMQ_Queues.mqsc file from the Scripts directory to /var/PMQ/MQSIFileInput/properties and Navigate to the IBMPMQ_Queues.mqsc location.

Type runmqsc pmqmanager, and press Enter.

Copy and paste the content of IBMPMQ_Queues.mqsc

Parent topic: Installing the ESB node artifact

Deploying BAR files

Bar files must be deployed to the broker pmqbroker with the execution group pmqgroup1.

Procedure

Log on to the Integration Bus node computer as the mqm user.

Navigate to the /opt/IBM/IS_ManEquipAuto_AssetAnalytics_1.0/BAR/ directory.

Enter the following command for PMQEventDataLoad.bar:

mqsideploy pmqbroker –e pmqgroup1 –a PMQEventDataLoad.bar

Enter the following command for MEAIntegration.bar:

mqsideploy pmqbroker –e pmqgroup1 –a MEAIntegration.bar

Parent topic: Installing the ESB node artifact

Source code files

The MEAIntegration_PI.zip file and PMQEventDataLoad_PI.zip file provide the source code for the IBM Integration Bus flow and code.

Note: All of the activities on the ESB node must be done using the mqm id. You must restart the pmqbroker service after you complete the activities.

Procedure

Copy both the MEAIntegration_PI.zip and PMQEventDataLoad_PI.zip files from the /opt/IBM/IS_MandEquipAuto_AssetAnalytics_1.0/Source directory.

Place the source files on the IIB node at /var/PMQ/MQSIFileInput/PMQSource.

Restart the pmqbroker service.

Parent topic: Installing the ESB node artifact

Deployment and Configuration of the SPSS Analytics Node

To prepare SPSS Collaboration and Deployment Services, you must set up links between the data in the database and the data used in the enterprise and in the application.

Before you begin

Ensure that following things are in place before importing content:

IBM SPSS Collaboration and Deployment Services Deployment Manager is installed on any client (windows) computer.

Copy the IS_MEA_CDS.pes file from the location where you deployed the solution on the Analytics node computer to the computer where IBM SPSS Collaboration and Deployment Services Deployment Manager is installed. The default installation directory for this file is /opt/IBM/xxxx/Analytics/. (Where xxxx is the installation directory provided at the time of installation)

/<...>/CN82XEN/SolutionInstaller/NodeRoot/Downloads/IS_ManEquipAuto_AssetAnalytics_1.0/Analytics

You know the admin credentials for the Predictive Analytics node, IBM DB2, and IBM SPSS Collaboration and Deployment Services.

An ODBC Connection for the PMQ database is created in the name of IBMPMQ in the Analytics node. If not then complete the following steps:

Right-click Data Sources, and click New > Data Source Definition .

In the Name box, enter IBMPMQ.

In the Type box, select ODBC Data Source.

Click Next.

In the DSN box, enter IBMPMQ.

Click Finish.

Note: An ODBC Connection for the PMQ database is created in the name of IBMPMQ in the Analytics node. This step is done by the content installer of PMQ. If there are issues related to ODBC connectivity, see the information on IBM SPSS Modeler - ODBC Configuration Best Practices and Troubleshooting in the IBM DeveloperWorks article: http://www.ibm.com/developerworks/library/ba-pp-spss-page660/

Procedure

Start Deployment Manager.

Click File > New > Content Server Connection .

In the Connection Name field, enter a name that identifies the Predictive Analytics node.

In the Server URL field, enter http://<analytics_node_IP>:<9080>/ and click Finish.

Right-click Content Repository, and click Import.

Browse to and select the IS_MEA_CDS.pes file.

Click Open.

Accept the default options in the Import window, and click OK. The Auto_Manufacturing_AA folder, two jobs in the Jobs folder, and two streams in the Modeler Streams folder are created.

Update the credential information for the Admin, db user (db2inst1), and root users so that the job and streams run successfully.

In the Content Explorer tab, under Resource Definitions, open the Credentials folder.

Update the Admin user with the credentials for the SPSS Collaboration and Deployment Services user that has access to the content repository and runs the job.

Update the db user (db2inst1) with the credentials for the user that has access to the IBM DB2 database.

Update the root user with the credentials for the user that has access to the Modeler Server.

Open the job in the Jobs folder and ensure that the user credentials match the credentials of the IBM DB2 instance on the ODBC tab.

There are two jobs that need to be executed. The Training Job creates the predictive models to be used by the Scoring Job. Therefore, the training job must be executed first.

Parent topic: Installation and configuration

Onboard equipment data

Custom flows are provided with the Asset Analytics for Manufacturing Equipment in Automotive solution. You use the custom flows to onboard equipment data and to trigger training and scoring models.

Master data and metadata must be loaded into the IBM Predictive Maintenance and Quality database, and you must also load the event data before you can run the analytic training or the scoring models.

Master data and metadata for the solution
You must provide the master data and metadata for the Asset Analytics for Manufacturing Equipment in Automotive solution. You must prepare the CSV files before you can load them into the environment.

Parent topic: Installation and configuration

Master data and metadata for the solution

You must provide the master data and metadata for the Asset Analytics for Manufacturing Equipment in Automotive solution. You must prepare the CSV files before you can load them into the environment.

The master data and metadata must be provided in the following CSV files:

language_upsert.csv

tenant_upsert.csv

event_code_upsert.csv

event_type_upsert.csv

group_dim_upsert.csv

location_upsert.csv

material_type_upsert.csv

measurement_type_upsert.csv

process_upsert.csv

product_upsert.csv

profile_calculation_upsert.csv

resource_type_upsert.csv

source_system_upsert.csv

supplier_upsert.csv

value_type_upsert.csv

material_upsert.csv

production_batch_upsert.csv

profile_variable_upsert.csv

resource_upsert.csv

The following examples show the contents that each of the CSV files that you prepare must contain.

The files group_dim_upsert.csv, location_upsert.csv, and resource_upsert.csv should be based on the equipment details, including its hierarchical relationship to other entities, and suited to your environment.

The solution provides for defining multilevel resource hierarchies that are augmented by group dimensions. A number of associations and relationships between resources and attributes can be defined. Any number of units of equipment can be defined, and associations can be defined to group them by any dimension; for example, OEM or Vendor can be defined as a dimension and associated with a unit of equipment.

Loading the master data and metadata
You must load the master data and metadata for the Asset Analytics for Manufacturing Equipment in Automotive solution in a specific order.

Parent topic: Onboard equipment data

Loading the master data and metadata

You must load the master data and metadata for the Asset Analytics for Manufacturing Equipment in Automotive solution in a specific order.

Procedure

Log in to the Integration Bus node computer as the mqm user.

Copy the files to the /var/PMQ/MQSIFileInput/masterdatain directory in the order that is shown in the following table:

Order
File name

1
language_upsert.csv

2
tenant_upsert.csv

3
event_code_upsert.csv

4
event_type_upsert.csv

5

group_dim_upsert.csv

6

location_upsert.csv

This file should be based on the location of the equipment.

7
material_type_upsert.csv

8
measurement_type_upsert.csv

9
process_upsert.csv

10
product_upsert.csv

11
profile_calculation_upsert.csv

12
resource_type_upsert.csv

13
source_system_upsert.csv

14
supplier_upsert.csv

15
value_type_upsert.csv

16
material_upsert.csv

17

production_batch_upsert.csv

18
profile_variable_upsert.csv

19
resource_upsert.csv

Important: The files must be copied one at a time.

For more information about master and metadata for IBM Predictive Maintenance and Quality, see the following topics in IBM Knowledge Center under Predictive Maintenance and Quality 2.5.1 :

Master data process

File format and location

The flat file API

Parent topic: Master data and metadata for the solution

Event data

Event data must also be loaded for the Asset Analytics for Manufacturing Equipment in Automotive solution.

Event data includes information such as maintenance data, and operational data.

The following image provides an example of the contents that each of the CSV files that you prepare must contain. The CSV files that you use should reflect your environment.

The example custom flows expect event and other supporting operational data in the formats shown in the image.

Onboarding event data
You must load the event data for the Asset Analytics for Manufacturing Equipment in Automotive solution.

Parent topic: Installation and configuration

Onboarding event data

You must load the event data for the Asset Analytics for Manufacturing Equipment in Automotive solution.

Procedure

Log in to the Integration Bus node computer as the mqm user.

Copy the event data files that you created to the directory: /var/PMQ/MQSIFileInput/eventdatain.

Parent topic: Event data

Deploying the IBM Cognos content

For IBM Cognos Business Intelligence, you must catalog the database, create a data source connection, and then deploy the content files for the IBM Asset Analytics for Manufacturing Equipment in Automotive solution.

Cataloging the IBMPMQ database
You must create a database connection to the IBMPMQ database in IBM Cognos Business Intelligence. Before you can create the connection, you must catalog the database in the IBM DB2 client.

Creating a data source connection to the IBMPMQ database
You create a data source connection using IBM Cognos Administration.

Moving the IBM Cognos content
As a root or sudo user, you must copy the IBM Cognos® content for the IBM Asset Analytics for Manufacturing Equipment in Automotive application to the appropriate locations in your IBM Cognos installation to be able to deploy the content.

Deploying the IBM Cognos reports
You must deploy the Asset Analytics for Manufacturing Equipment in Automotive reports by using IBM Cognos Administration.

Opening the Framework Manager model
You can view the Asset Analytics for Manufacturing Equipment in Automotive dashboard model in IBM Cognos Framework Manager. The Framework Manager project file (.cpf) for the Capacity Management Analytics model is included in the MEA_FMProject.zip file.

Parent topic: Installation and configuration

Cataloging the IBMPMQ database

You must create a database connection to the IBMPMQ database in IBM Cognos Business Intelligence. Before you can create the connection, you must catalog the database in the IBM DB2 client.

Procedure

Log on to the Business Intelligence node computer, and change to the db2inst1 user.

For example, in a terminal window, type su db2inst1.

Enter the following command to catalog the database server:

db2 "catalog tcpip node OP( <Nodename>) remote DB2_server_name server DB2_port_number"

Note: The Nodename cannot be more than 8 characters.

Enter the following command to catalog the IBMPMQ database:

db2 "catalog database IBMPMQ as IBMPMQ at node OP( <Nodename>)"

Enter the following command to ensure that the database was cataloged correctly:

db2 list database directory

IBMPMQ should appear in the list.

Parent topic: Deploying the IBM Cognos content

Creating a data source connection to the IBMPMQ database

You create a data source connection using IBM Cognos Administration.

Procedure

Open a web browser.

Go to the IBM® Cognos® BI portal URL.

For example, go to http://binodename/ibmcognos/.

On the Welcome page, click Administer IBM Cognos Content .

Click the Configuration tab, and click Data Source Connections .

Click the New Data Source icon New data source icon.

In the Name box, type IBMPMQ, and then click Next.

In the connection page, select IBM DB2, ensure that Configure JDBC connection is selected, and click Next.

In the DB2 database name field, type IBMPMQ.

Leave DB2 connect string blank.

Under Signons, select both Password and Create a signon that the Everyone group can use, and then type the user ID and password for the DB2® instance owner user that you used to create the database, and click Next.

For example, enter db2inst1 and the appropriate password.

Tip: To test whether the parameters are correct, click Test the connection . After you test the connection, click OK to return to the connection page.

In the Server name box, enter the name or IP address of your IBM DB2 server computer.

In the Port number box, enter the DB2 port number. The default is 50000.

In Database name, type IBMPMQ.

Tip: To test whether the parameters are correct, click Test the connection . After you test the connection, click OK to return to the connection page.

Click Finish.

Parent topic: Deploying the IBM Cognos content

Moving the IBM Cognos content

As a root or sudo user, you must copy the IBM® Cognos® content for the IBM Asset Analytics for Manufacturing Equipment in Automotive application to the appropriate locations in your IBM Cognos installation to be able to deploy the content.

Procedure

Copy the IBM Cognos content from the computer where you deployed the Asset Analytics for Manufacturing Equipment in Automotive Business Intelligence content to the <BI_Install_location>\deployment folder on the Business Intelligence node computer.

The Asset Analytics for Manufacturing Equipment in Automotive IBM Cognos content file is named MEA_BIContent.zip .

Copy the IBM Cognos report image file to the <BI_Install_location>\webcontent\Images directory on the Business Intelligence node computer and decompress it.

You must create the Images directory if it does not already exist.

The report images file is named MEA_Images.zip .

Copy the IBM Cognos map specification file to the Business Intelligence node install location.

Copy the IBM Cognos Framework Manager model file to the Business Intelligence node install location.

If you want to edit the Framework Manager models, you must catalog the Asset Analytics for Asset Analytics for Manufacturing Equipment in Automotive database on the computer where Framework Manager is installed.

Parent topic: Deploying the IBM Cognos content

Deploying the IBM Cognos reports

You must deploy the Asset Analytics for Manufacturing Equipment in Automotive reports by using IBM® Cognos® Administration.

Procedure

Open a web browser.

Go to the IBM Cognos BI portal URL ( http:// <ibmcognos_node_IP>/ibmcognos/ ).

On the Welcome page, click Administer IBM Cognos Content .

On the Configuration tab, click Content Administration .

On the toolbar, click the New Import button.

In the Deployment Archive pane, select the deployment archive, and click Next.

The deployment archive is named MEA_BIContent.zip .

In the Specify a name and description pane, accept the default or enter a new name, and click Next.

In the Select the public folders and directory content pane, select all of the packages in the table, leave the Options as default, and click Next.

Note: Ensure that the Disable after import option is cleared.

In the Specify the general options pane, accept the defaults, and click Next.

On the Review the summary page, click Next.

On the Select an action page, select Save and run once , and click Finish.

On the Run with options page, accept the defaults, and click Run, and then click OK.

Select View the details of this import after closing this dialog and click OK.

Note: RAVE content is also imported as part of the MEA_BIContent import.

Parent topic: Deploying the IBM Cognos content

Opening the Framework Manager model

You can view the Asset Analytics for Manufacturing Equipment in Automotive dashboard model in IBM® Cognos® Framework Manager. The Framework Manager project file (.cpf) for the Capacity Management Analytics model is included in the MEA_FMProject.zip file.

Procedure

Start IBM Cognos Framework Manager.

From the Welcome page, click Open a project .

Navigate to the folder where you decompressed the MEA_FMProject.zip file, and select the IBMPMQ_Model.cpf file.

Click Open.

If you must republish the packages, you must update the Tenant_Id in the Tenant_lookup parameter in the model.

You can find the Tenant_Id in the IBMPMQ database by using the following database query:

Select Tenant_Id from pmqsch.tenant where Tenant_cd='B&W'

After you have made changes to the model, you can republish the package.

In the Project Viewer pane, expand Packages.

Right-click the package, and click Publish Package.

After publishing, the package should be available in Public Folders > MEA_AssetAnalytics in the IBM Cognos Business Intelligence portal.

Parent topic: Deploying the IBM Cognos content

Data flows and orchestration

This section describes the data model and data flows that are used for the IBM Asset Analytics for Manufacturing Equipment in Automotive solution.

Data mapping
This topic provides data mapping information for the IBM Asset Analytics for Manufacturing Equipment in Automotive solution.

Data input flow
For input data loading, standard master data and event data loading flows are used. The orchestration file PMQ_orchestration_definition_mea.xml placed under /var/mqsi/shared-classes/orchestrations on the IIB node orchestrates the flow of output data.

Data output flow
Output from the analytical model is stored in the PMQ data store through standard event loading IIB flows as provided by IBM Predictive Maintenance and Quality 2.5.1. The orchestration file PMQ_orchestration_definition_mea.xml placed under /var/mqsi/shared-classes/orchestrations on the IIB node orchestrates the flow of output data.

Training model triggering flow
Training invocation is scheduler based.

Scoring model triggering flow
The scoring model is responsible for generate the Health Score for the set of equipment based upon the maintenance and event data associated with that equipment.

Data mapping

This topic provides data mapping information for the IBM Asset Analytics for Manufacturing Equipment in Automotive solution.

Tables used in the solution

Table 1. Tables used in the Solution

Table Name
Comments

CALENDAR
Auto populated during content installation.

EVENT_TIME
Auto populated during content installation.

TENANT
PMQ as the default tenant will be populated in this table.

LANGUAGE
English (EN) will be populated as the default language in this table.

MASTER_LOCATION
Site information will be populated in this table.

MASTER_SOURCE_SYSTEM
This table will be populated with the following values:

SENSOR – To be used for sensor data.

PREDMAIT – To be used for model output.

MASTER_MEASUREMENT_TYPE
This table will be populated with the following values:

FAIL – For capturing failure event of the robot.

WARN– For capturing warning event of the robot

PM – For capturing Preventive Maintenance performed on the robot.

CM – For capturing Corrective Maintenance performed on the robot.

Confidence in Prediction - For capturing SPSS model output

Predicted Hours To Fault – For capturing SPSS model output.

Predicted Duration of Fault – For capturing SPSS model output.

Predicted Fault – For capturing SPSS model output.

Trigger Event – For capturing SPSS model output.

RECOMMENDED_ACTION – For capturing recommended actions. Currently six variables are created to capture six actions.

MASTER_EVENT_TYPE
This table will be populated with the following values:

BODYWELD – Used to identify failure and warning input events.

MNT – Used to identify maintenance input events.

BODYWELDRC – Used to identify SPSS output events.

MASTER_EVENT_CODE
The table will be populated with the observation text (type of failure/warning) associated with failure and warning events. This table will be populated automatically when the event data is loaded.

MASTER_VALUE_TYPE
The table will be populated with ACTUAL and FORECAST values.

MASTER_PROFILE_CALCULATION
This table will be populated with ASSIGN and Measurement of Type Count calculation.

MASTER_PROFILE_VARIABLE
This table will be populated for capturing failure and warning count based on the type of failure and warning respectively. It will capture the most recent values of SPSS model output. The following variables will be created:

FAIL_COUNT

WARN_COUNT

Confidence in Prediction

Predicted Hours To Fault

Predicted Duration of Fault

Predicted Fault

Trigger Event

System Health Indicator

RECOMMENDED_ACTION1

RECOMMENDED_ACTION2

RECOMMENDED_ACTION3

RECOMMENDED_ACTION4

RECOMMENDED_ACTION5

RECOMMENDED_ACTION6

MASTER_GROUP_DIM
The following group dimension levels of resources are used for capturing the hierarchy of resource:

Group Type 1 – Work Cell

Group Type 2 – Manufacturing Line

Group Type 3 – Area

Group Type 4 – Enterprise

MASTER_RESOURCE_TYPE
The table will be populated with ASSET and AGENT values.

MASTER_RESOURCE
Used to capture robot details including model and serial number.

KEY_LOOKUP
Will be auto populated by PMQ during insertion of master data.

EVENT & EVENT_OBSERVATION
Maintenance data available will be populated in these tables.

RESOURCE_KPI
Daily aggregated count of failure and warning event for each resource based on the type of failure and warning is populated in this table.

EVENT_PROFILE
Output values from SPSS model for the profile variables such as Confidence in Prediction and Predicted Hours To Fault are populated in this table.

RESOURCE_PROFILE
Most recent output values from SPSS model are populated here.

Parent topic: Data flows and orchestration

Data input flow

For input data loading, standard master data and event data loading flows are used. The orchestration file PMQ_orchestration_definition_mea.xml placed under /var/mqsi/shared-classes/orchestrations on the IIB node orchestrates the flow of output data.

Load master data by copying master data files in appropriate sequence to the /var/PMQ/MQSIFileInput/masterdatain folder.

Load event data by copying event data files to the /var/PMQ/MQSIFileInput/eventdatain folder.

Parent topic: Data flows and orchestration

Data output flow

Output from the analytical model is stored in the PMQ data store through standard event loading IIB flows as provided by IBM Predictive Maintenance and Quality 2.5.1. The orchestration file PMQ_orchestration_definition_mea.xml placed under /var/mqsi/shared-classes/orchestrations on the IIB node orchestrates the flow of output data.

Parent topic: Data flows and orchestration

Training model triggering flow

Training invocation is scheduler based.

Schedule the training of SPSS streams by setting the appropriate scheduler/webservice configuration (scheduled_time, duration_in_days, url) in PMQ_orchestration_definition_batch.xml for orchestration with identifier MEATraining.

MEAIntegration along with standard batch orchestration is used for training model invocation.

Parent topic: Data flows and orchestration

Scoring model triggering flow

The scoring model is responsible for generate the Health Score for the set of equipment based upon the maintenance and event data associated with that equipment.

Invocation of scoring model will done at the end of every input file (Failure and Warning data file) loading.

Invocation of scoring model will happen sequentially by using a queue based mechanism in IIB after verifying that previous job invocation has ended.

MEAIntegration along with standard batch orchestration is used for scoring model invocation.

For scoring model, set the Webservice configuration (url) in PMQ_orchestration_definition_batch.xml for orchestration with identifier MEA.

For the first time data load, invocation of the scoring model will wait until the training is complete.

Parent topic: Data flows and orchestration

Overview of the analytics model

IBM Predictive Maintenance and Quality 2.5.1 is used as the underlying platform for the solution. IBM SPSS Modeler 17.0, which is part of the Predictive Maintenance and Quality 2.5.1 platform, is used as the predictive modeling tool. There are two SPSS streams which are created. One stream for the training and creation of the predictive model and another stream for using the predictive models and scoring the new incoming events.

Training model
Predictive models must be trained to determine which data is useful and which data is not needed.

Scoring model
The SPSS Scoring Job is orchestrated by a script. The script retrieves the latest training models from the repository.

CADS Jobs
Two jobs are created in SPSS CADS. One is invoked for training the model, and another is invoked while scoring the job. The IIB flows use the Object URI in CADS to invoke these jobs.

Training model

Predictive models must be trained to determine which data is useful and which data is not needed.

Input tables used by predictive models

The following input tables are used for the creation and scoring of the predictive models:

PMQSCH.EVENT – Provides all the Input Event Ids

PMQSCH.EVENT_OBSERVATION – Provides the observation values related to the events

PMQSCH.MASTER_RESOURCE – Provides the resource details of the assets

PMQSCH.MASTER_VALUE_TYPE – This table along with event observation is used to identify only Actual Values for predictive models

PMQSCH.MASTER_MEASUREMENT_TYPE – This table along with event observation is used to identify only Warnings and Failures from the Event observation

Modeling approach

The observation from each event is collected and summarized with all the events that occurred from the previous fault. This information is then used to identify the next fault that is to occur. The Auto Classifier node is used to identify the next likely fault.

The Auto Classifer node provides the next likely fault failure and the confidence associated with the prediction. The Auto Classifier node estimates and compares models for all the faults as targets, using a number of different methods in a single modeling run. The node explores every possible combination of options, ranks each candidate model based on the measure specified, and saves the best models for use in scoring or further analysis.

An Auto Numeric node is used to estimate the time to fault. The Auto Numeric node estimates and compares models for the time to fault using a number of different methods. The node explores every possible combination of options, ranks each candidate model based on the correlation, and saves the best for use in scoring or further analysis.

The SPSS Stream is orchestrated by the SPSS Script. The SPSS Script initially runs the Job Status Update to identify the orchestration that a SPSS stream is running. The SPSS stream then joins all the relevant tables and prepares the data for modeling. After all the input data is present, the Stream creates derived variables which will serve as the target. The first derived variable scans all the variables and identifies the next Fault and calculates the duration taken for the fault to actually occur. Then the time taken for the system to come up is also calculated.

Then the SPSS Script refreshes the type node and restructure node, which creates the derived variables for prediction. After columns for each failure are created, a running counter is set for each column. After all the derived variables are created, the predictive models are created based on the training data.

Parent topic: Overview of the analytics model

Scoring model

The SPSS Scoring Job is orchestrated by a script. The script retrieves the latest training models from the repository.

The Scoring model also keeps track of the last analyzed failure. The data from the last analyzed failure is used for future failure predictions. Once the data is scored, the data rows are prepared corresponding to the IBM Predictive Maintenance and Quality format so that IIB orchestrations can take the latest scores and update them in the database.

Parent topic: Overview of the analytics model

CADS Jobs

Two jobs are created in SPSS CADS. One is invoked for training the model, and another is invoked while scoring the job. The IIB flows use the Object URI in CADS to invoke these jobs.

Parent topic: Overview of the analytics model

Using Asset Analytics for Manufacturing Equipment in Automotive

The IBM Asset Analytics for Manufacturing Equipment in Automotive solution provides insights into the functioning of robotic equipment. Dashboards provide maintenance operators with visualizations that indicate the status of equipment and provide predictions about when equipment will fail.

The solutions provides the following reports:

Landing page, which provides a visual representation of the robotic equipment and an indication of the health of each piece of equipment.

Maintenance Dashboard, which provides information about a selected piece of equipment, including the maintenance history, current health, and recommended actions.

Equipment Specification, which provides specification details for the selected piece of equipment.

An example of using the solution
A maintenance operator can use the Asset Analytics for Manufacturing Equipment in Automotive to monitor the health of each piece of equipment and identify machines that are in need of maintenance.

An example of using the solution

A maintenance operator can use the Asset Analytics for Manufacturing Equipment in Automotive to monitor the health of each piece of equipment and identify machines that are in need of maintenance.

About this task

This task describes how a maintenance operator uses the solution to identify a piece of robotic equipment that requires maintenance and determine the appropriate action. The screen shots shown are for example purposes and will vary depending on your implementation of the solution.

Procedure

Connect to the solution.

The Landing page shows the status of each machine and the overall system health.

Click a machine to display its respective Maintenance Dashboard.

The Maintenance Dashboard provides the following details about the piece of equipment:

Production Site View, which shows the layout and status of the equipment.

Equipment Data, which provides equipment hierarchy data and equipment identifiers, including recent 30 failure probability scores, predicted time to failure, predicted faults, and so on.

Recommended Actions

Time Series Analysis, which includes error frequency distribution and maintenance record. You can set the period to filter the information shown on this report.

To view specifications for the selected piece of equipment, click the Dossier button.

The Equipment Specification report is shown.

Parent topic: Using Asset Analytics for Manufacturing Equipment in Automotive

Accessibility features

Accessibility features help users who have a physical disability, such as restricted mobility or limited vision, to use information technology products.

For information about the commitment that IBM has to accessibility, see the IBM Accessibility Center (www.ibm.com/able).

IBM Cognos HTML documentation has accessibility features. PDF documents are supplemental and, as such, include no added accessibility features.

Report output

In IBM Cognos Administration, you can enable system-wide settings to create accessible report output. For more information, see the IBM Cognos Business Intelligence Administration and Security Guide . In IBM Cognos Report Studio, you can enable settings to create accessible output for individual reports. For more information, see the IBM Cognos Report Studio User Guide . You can access the previously mentioned documents at IBM Knowledge Center (http://www.ibm.com/support/knowledgecenter).

Troubleshooting

This section contains troubleshooting information for the Asset Analytics for Manufacturing Equipment in Automotive installation.

Troubleshooting a problem
Troubleshooting is a systematic approach to solving a problem. The goal of troubleshooting is to determine why something does not work as expected and how to resolve the problem.

Troubleshooting resources
Troubleshooting resources are sources of information that can help you resolve a problem that you are having with an IBM® product.

Supported web browsers
The solution installer runs on Google Chrome 44, or later, or Mozilla Firefox 38 or later web browsers.

Troubleshooting a problem

Troubleshooting is a systematic approach to solving a problem. The goal of troubleshooting is to determine why something does not work as expected and how to resolve the problem.

Review the following table to help you or customer support resolve a problem.

Table 2. Troubleshooting actions and descriptions .

Actions | Description
A product fix might be available to resolve your problem. | Apply all known fix packs, or service levels, or program temporary fixes (PTF).
Look up error messages by selecting the product from the IBM Support Portal, and then typing the error message code into the Search support box (http://www.ibm.com/ support/entry/portal/). | Error messages give important information to help you identify the component that is causing the problem.
Reproduce the problem to ensure that it is not just a simple error. | If samples are available with the product, you might try to reproduce the problem by using the sample data.
Ensure that the installation successfully finished. | The installation location must contain the appropriate file structure and the file permissions. For example, if the product requires write access to log files, ensure that the directory has the correct permission.
Review all relevant documentation, including release notes, technotes, and proven practices documentation. | Search the IBM Knowledge Center to determine whether your problem is known, has a workaround, or if it is already resolved and documented.
Review recent changes in your computing environment. | Sometimes installing new software might cause compatibility issues.

If the items in the table did not guide you to a resolution, you might need to collect diagnostic data. This data is necessary for an IBM® technical-support representative to effectively troubleshoot and assist you in resolving the problem. You can also collect diagnostic data and analyze it yourself.

Parent topic: Troubleshooting

Troubleshooting resources

Troubleshooting resources are sources of information that can help you resolve a problem that you are having with an IBM® product.

Support Portal

The IBM Support Portal is a unified, centralized view of all technical support tools and information for all IBM systems, software, and services.

The IBM Support Portal lets you access all the IBM support resources from one place. You can tailor the pages to focus on the information and resources that you need for problem prevention and faster problem resolution. Familiarize yourself with the IBM Support Portal by viewing the demo videos (https://www.ibm.com/blogs/SPNA/entry/the_ibm_support_portal_videos).

Find the content that you need by selecting your products from the IBM Support Portal (http://www.ibm.com/support/entry/portal).

Before contacting IBM Support, you will need to collect diagnostic data (system information, symptoms, log files, traces, and so on) that is required to resolve a problem. Gathering this information will help to familiarize you with the troubleshooting process and save you time.

Service request

Service requests are also known as Problem Management Reports (PMRs). Several methods exist to submit diagnostic information to IBM Software Technical Support.

To open a PMR or to exchange information with technical support, view the IBM Software Support Exchanging information with Technical Support page (http://www.ibm.com/software/support/exchangeinfo.html).

Fix Central

Fix Central provides fixes and updates for your system's software, hardware, and operating system.

Use the pull-down menu to navigate to your product fixes on Fix Central (http://www.ibm.com/systems/support/fixes/en/fixcentral/help/getstarted.html). You may also want to view Fix Central help.

IBM developerWorks

IBM developerWorks® provides verified technical information in specific technology environments.

As a troubleshooting resource, developerWorks provides easy access to the most popular practices, in addition to videos and other information: developerWorks (http://www.ibm.com/developerworks).

IBM Redbooks

IBM Redbooks® are developed and published by the IBM International Technical Support Organization, the ITSO.

IBM Redbooks (http://www.redbooks.ibm.com) provide in-depth guidance about such topics as installation and configuration and solution implementation.

Software support and RSS feeds

IBM Software Support RSS feeds are a quick, easy, and lightweight format for monitoring new content added to websites.

After you download an RSS reader or browser plug-in, you can subscribe to IBM product feeds at IBM Software Support RSS feeds (https://www.ibm.com/software/support/rss).

Log files

Log files can help you troubleshoot problems by recording the activities that take place when you work with a product.

Error messages

The first indication of a problem is often an error message. Error messages contain information that can be helpful in determining the cause of a problem.

Parent topic: Troubleshooting

Supported web browsers

The solution installer runs on Google Chrome 44, or later, or Mozilla Firefox 38 or later web browsers.

Solution users who choose to use IE 10 as the browser of preference, is highly recommended to follow the steps documented in the technote below, for best visualization. https://technet.microsoft.com/en-us/library/dn872481.aspx

Note: Please make sure to have set the correct path of the xml file create, in the registry entry (If you have opted to turn ON the Enterprise Mode using the registry).

Tip: For more information, see http://www-01.ibm.com/support/docview.wss?uid=swg21672432

Parent topic: Troubleshooting

Solution extensions

This appendix provides information on extensions to the Asset Analytics for Manufacturing Equipment in Automotive solution.

Addition of new equipment and assets
Other equipment and assets can be loaded for the IBM Asset Analytics for Manufacturing Equipment in Automotive solution so that Time-To-Failure metrics for them can be calculated.

Customize report or create new reports
Customers can customize reports or create new reports for a configured asset by using IBM Cognos Report Studio and IBM Cognos Framework Manager.

Customize predictive models
You can develop your own predictive models using any other modeling tools and input data. Input data other than the warning and faults includes information such as parametric data, repair data, product data, environmental data, and so on. According to your data mapping needs, the orchestration can be customized.

Integration with asset management and manufacturing execution systems
Customers can extend the solution to integrate with Asset management solutions

System health indicator
The system health indicator is an indicator of overall health of the automotive assembly that consists of more than one asset. The system is assumed to consist of several independent components and a failure of any one component results in a failure of the system. The system is represented by a series reliability block diagram. In general, for a series of nindependent assets or equipment, the system health indicator or system reliability is as show below. This is known as the product rule.

Addition of new equipment and assets

Other equipment and assets can be loaded for the IBM Asset Analytics for Manufacturing Equipment in Automotive solution so that Time-To-Failure metrics for them can be calculated.

Equipment or Asset other than weld robot includes pallet conveyor, material handling robot, inspection robot, lift truck, sensor, weld gun, welding fixture, pneumatic clamp, etc. Following steps need to be followed for configuring the system with the new asset:

Master data for the new asset needs to be loaded.

Define Resource, resource type & attributes

In case the asset is located at a new location, define the new location

Note: For more information on loading new master data into PMQ please refer to PMQ documentation: http://www-01.ibm.com/support/knowledgecenter/SSTNNL_2.5.1/com.ibm.swg.ba.cognos.pmq_solution_guide.2.5.1.doc/c_conf_md_pmq.html?lang=en

Load historical failure data, warning data and maintenance data for the new equipment

The resource landing page would need to be updated to reflect the new equipment

Note: In case of a different type of input event data altogether, a new predictive model has to be built and would also involve changes to orchestration.

Parent topic: Solution extensions

Customize report or create new reports

Customers can customize reports or create new reports for a configured asset by using IBM Cognos Report Studio and IBM Cognos Framework Manager.

Verify whether the Business Intelligence layer supports the required Framework Manager model necessary for the report that is being developed. If it does not, you must make changes to the provided model by using IBM Cognos Framework Manager.

Some examples of customizations include:

All error code occur in a month

Particular error code happened over a time

Particular error code (FALT / WARNING) repeated for preventive maintenance over a time

Inclusion of other useful metrics and graphical representation for the predictive model

Customers can as well use any other reporting technology and leverage PMQ data model for retrieving data information. For more details on PMQ data model schema, please refer to the PMQ Solution guide at: http://www-01.ibm.com/support/knowledgecenter/SSTNNL_2.5.1/com.ibm.swg.ba.cognos.pmq_solution_guide.2.5.1.doc/c_conf_md_pmq.html?lang=en

Parent topic: Solution extensions

Customize predictive models

You can develop your own predictive models using any other modeling tools and input data. Input data other than the warning and faults includes information such as parametric data, repair data, product data, environmental data, and so on. According to your data mapping needs, the orchestration can be customized.

The current solution’s predictive model uses fault data, warning data, and maintenance data for predictions. The predictability of the model can be enhanced further by identifying new parametric data. If such new parametric data is available, then complete the following steps:

Load the meta-data related to this parametric data. For more information about loading master data into IBM Predictive Maintenance and Quality, refer to the Predictive Maintenance and Quality Solution guide at: http://www-01.ibm.com/support/knowledgecenter/SSTNNL_2.5.1/com.ibm.swg.ba.cognos.pmq_solution_guide.2.5.1.doc/c_conf_md_pmq.html?lang=en

Load actual parametric data. For more information about loading event data into Predictive Maintenance and Quality, refer to the Predictive Maintenance and Quality Solution guide at: http://www-01.ibm.com/support/knowledgecenter/SSTNNL_2.5.1/com.ibm.swg.ba.cognos.pmq_solution_guide.2.5.1.doc/c_conf_measure_pmq.html?lang=en

Use IBM SPSS Modeler to retrieve the model from IBM SPSS Collaboration & Deployment Services’ deployment manager. Open and modify the training and scoring streams of this solution as necessary.

Again use IBM SPSS Collaboration & Deployment Services to redeploy the updated stream into the environment. Save the respective jobs.

Note: It is best to verify and test any change in the model or orchestration flows thoroughly in a staging environment before moving it to a production environment.

Parent topic: Solution extensions

Integration with asset management and manufacturing execution systems

Customers can extend the solution to integrate with Asset management solutions

Integrating the solution with other asset management systems can be done by using the connectivity and data transformation capabilities of IBM Integration Bus (IIB). This involves creation of new message flows in IIB. The solution includes a prebuilt adapter for integration with the IBM Maximo asset management system. For more details, refer to the Predictive Maintenance and Quality documentation on IBM Knowledge Center.

Parent topic: Solution extensions

System health indicator

The system health indicator is an indicator of overall health of the automotive assembly that consists of more than one asset. The system is assumed to consist of several independent components and a failure of any one component results in a failure of the system. The system is represented by a series reliability block diagram. In general, for a series of nindependent assets or equipment, the system health indicator or system reliability is as show below. This is known as the product rule.

System health = Π Ri, where i = 1 to n and R is the reliability of an asset (probability that the asset doesn’t fail for a given time)

Parent topic: Solution extensions

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Parent topic: Notices