Spruik/Libre - Githubissues

Open source Manufacturing Execution and Performance Monitoring built on Grafana, Influx, and Postgres.

Define your master data, push your machine metrics, start collecting and analyzing your manufacturing data with Libre. Libre is an open source manufacturing execution and performance monitoring tool.

Define: Your manufacturing master data including your enterprise model, downtime reasons, products, ingredients and product steps.
Capture: Connect up your machines using a variety of methods into key buckets with an InfluxDB Historian
Use: Schedulers create and schedule orders, operators execute orders and capture downtime reasons.
Improve: Get key insights into your manufacturing, understand your biggest losses, visualize OEE.
Extensible: Built on Grafana, Influx and postgres push your key process parameters to view alongside your production dashboards. Extend with your Grafana dashboards. Free to innovate.

Libre

Try it out

Use the Libre Simulator to test out Libre. The quickest way to run Libre and the Libre Simulator it is with the docker-compose command docker-compose -f docker-compose.yml -f docker-compose.sim.yml up -d. This will start up Libre and the simulator together. After running the command, browse to http://localhost:3000 to access Grafana and http://localhost:1880/ui to control the simulation.

See Try it out for more information.

Getting Started

Installation

Libre requires the following on an x86 architecture server

docker (>= 18 required)
docker-compose (>= 1.25 required)
git (>= 2 optional)

The docker-compose.yml file is required to start. Easiest way to get this is to clone this repository.

$ git clone https://github.com/Spruik/Libre

Cloning into 'Libre'...
remote: Enumerating objects: 165, done.
remote: Counting objects: 100% (165/165), done.
remote: Compressing objects: 100% (115/115), done.

Receiving objects: 100% (165/165), 176.45 KiB | 3.60 MiB/s, done.
Resolving deltas: 100% (49/49), done.

$ docker-compose up -d
Creating network "libre_default" with the default driver
Creating volume "libre_grafana_plugins" with default driver
Creating volume "libre_grafana_provisioning" with default driver
Creating volume "libre_postgres_data" with default driver
Creating volume "libre_influx_data" with default driver
Creating libre_influx_1   ... done
Creating libre_postgres_1 ... done
Creating libre_grafana_1  ... done
Creating libre_postREST_1 ... done

Set Grafana Admin Password

Once Libre is installed and running, navigate to http://<server>:3000/ and use the default Grafana login username admin and password admin to login. You will then be prompted to change the default password.

Define your factory Model

Define your factory model using the provided SmartFactory/Master Data dashboard. Start by long-clicking the Enterprise in the equipment panel and add a Site. Long-click the newly created site and add an Area. Continue this process to add in a Line and equipment on the line. Add in any additional Sites, area, lines and equipment to mimic your enterprise.

Equipment

Next, define your reason codes. Long click ReasonCodes in the Reason Codes panel and add a category. Once a category has been created, long click the category to add in a reason.

Two recommend categories are Planned and Unplanned

Reason Codes

Raw Materials are added during product operations. Products are made up of a number of product operations. Finally, products can be categorized by groups. Start by entering in Raw Material information by clicking the (+) on the Raw Material panel. These are the ingredients that go into your final product. Once raw materials have been added, add in the required Product Operations in the Product Operation panel. Product Operations are the steps to manufacture the final product and is where a raw ingredient is added. For example Fill Tank or Add Label.

Raw Materials

Product Operations

Once Raw Materials and Product Operations are added create a Product group using the Products Panel. Click the (+) and select Product Group, enter a name and save. Follow the same process and select Product. You can now add any number of product operations, and optionally an ingredient, to the product definition. At a minimum provide a product name, product group and save. Repeat for all your products.

Products

Now that you have defined your factory model, downtime reasons, ingredients, product operations and products your are ready to start scheduling orders.

Scheduling Orders

Schedule orders on your lines using the SmartFactory/Scheduling dashboard. To setup use the Production Line Start Time Setter to define the start time for each line. This is the time whereby an order will be first scheduled for the day. For 24hr operation, set to 12:00AM.

Use the Scheduler Order Management Table panel to create orders. Click the (+) define the order details and submit. Orders can be edited until they are released. Once an order has been released it can no longer be edited. Orders are edited by clicking in them in the panel.

Scheduler Table

Orders have the following state model:

Libre Order State Model

The SmartFactory/Line Schedule dashboard shows the schedule for the selected manufacturing line. Orders can be set to next/running so that they are visible on the SmartFactory/Line Performance dashboard.

Executing Orders

Orders be executed by clicking from the list in either SmartFactory/Line Performance or SmartFactory/Line Schedule and selecting Running. Only a single order can be Running at once per line. The Paused state can be used to pause orders until they are ready to be execute on again or completed. Once an order is running machine state and counts are logged against that order.

Integrating Machines

Machines will need to push data to the following buckets and schemas. Some integration templates are also provided within this repository.

Availability

The machine will need to publish to the Availability Influx bucket with the following information. It is important that the tags match the model definition. Log data on state change. category, reason, parentReason and comment are for classification of downtime category/reason. The Machine can self report (if known), otherwise leave blank. An operator can always split a reason and override

Name	Type	Variable Type	Details
Site	tag	string
Area	tag	string
Line	tag	string
idle	field	number	∈ [1, 0] for active / not active
stopped	field	number	∈ [1, 0] for active / not active
held	field	number	∈ [1, 0] for active / not active
execute	field	number	∈ [1, 0] for active / not active
complete	field	number	∈ [1, 0] for active / not active
status	field	string	String - ∈ ['idle', 'stopped', 'held', 'execute', 'complete']. String representation of state
category	field	string	Label of the category
reason	field	string	Label of the reason
parentReason	field	string	Child reason of the category (same reason as above)
comment	field	string	Comment on the reason

Performance

The machine will need to publish to the Performance Influx bucket with the following information. It is important that the tags match the model definition. Log data on state, planned rate or a significant actual_rate change. Ensure to use identical units for planned_rate and actual_rate.

Name	Type	Variable Type	Details
Site	tag	string
Area	tag	string
Line	tag	string
idle	field	number	∈ [1, 0] for active / not active
stopped	field	number	∈ [1, 0] for active / not active
held	field	number	∈ [1, 0] for active / not active
execute	field	number	∈ [1, 0] for active / not active
complete	field	number	∈ [1, 0] for active / not active
status	field	string	String - ∈ ['idle', 'stopped', 'held', 'execute', 'complete']. String representation of state
planned_rate	field	float	The planned rate or line theoretically best possible rate
actual_rate	field	float	The actual machine rate

Quality

The machine will need to publish to the Quality Influx bucket with the following information. It is important that the tags match the model definition. Log data on state, planned rate or a significant actual_rate change.

Name	Type	Variable Type	Details
Site	tag	string
Area	tag	string
Line	tag	string
Temp	field	number	Quantity of good product this order

Order Performance

The machine will need to publish to the OrderPerformance Influx bucket with the following information. Log data on issued_qty change. Note that order_id and product_id must match to update the current order panel.

Name	Type	Variable Type	Details
order_id	tag	string	Current order id
product_id	tag	string	Current product id
issued_qty	field	number	Count of good products this order

Analyzing the Manufacturing Data

Analyse your manufacturing data using the SmartFactory/Line Performance and SmartFactory/Analysis dashboards. Line Performance offers analysis of performance and availability whilst the Analysis dashboard drills into time loss through Downtime Pareto graphs and sunbursts of both Downtime duration and frequency.

Developing

Prerequisites

docker (>= 18 required)
git (>= 1.20 required)

Run the docker compose with the docker-compose.dev.yl file. Include the --build argument to build containers from source. docker-compose -f docker-compose.dev.yml up --build
To clear data whilst developing ensure to remove volumes docker-compose -f docker-compose.dev.yml rm -v

Building