Quality Control Implementation Guide

Implementing AlisQI might be a bit overwhelming at first: where to start?

Luckily, AlisQI is designed to be implemented by the users themselves. The system offers a few building blocks that you can use to reflect your process and controls.

In order to help you to define the right setup for your organization, we developed this guide. This guide presents an overview of the steps to take in analyzing your process, and discusses several implementation alternatives. This is illustrated by means of an example case that will put the implementation alternatives in context.

The primary steps in analyzing your processes and defining your AlisQI setup are:

  1. Primary process
    Determine your primary process (preferably by flowchart)
  2. Sampling points
    Define the sampling points within your process
  3. Registrations
    Per sampling point:
    1. Determine what general information should be recorded (name, article, batch number, machine et cetera)
    2. Determine which product characteristics should be analyzed
  4. Setting up analysis-sets
    1. Need to know
    2. Creating analysis-sets
  5. Collect historical data & import in AlisQI
  6. Input specification per analysis-set

Example: John's Bakery
John’s Bakery is growing rapidly. John had to hire more staff in order to meet with market demand. John’s Bakery is a business to business deliverer. The high quality of his bread is his unique selling point. Therefore he needs a quality system which is easy-to-use and which facilitates users to comply with John’s quality processes. John chose AlisQI as the quality platform for his business. Let’s get started implementing AlisQI for John!

1. Primary process

The first thing we do is determining our primary process. Since this process is the core of your organization it is important that AlisQI is aligned with this process.

The primary process of John’s Bakery is as follows.

Before, during or after some of these steps analyzes have to be conducted to ensure the quality of John’s products. Let’s define these sampling points to get a clear view of where quality control is involved.

2. Sampling points

Sampling points often have different characteristics. The analyzer, analytic values or just descriptive information could differ per sampling point. The first step is to define each sampling point.

At John’s Bakery there are four different sampling points.

As you can see Quality Control validates the products at four distinct moments during the process:

  1. At Raw material reception
  2. After mixing
  3. After proofing
  4. At Final product (bread)

3. Registrations

Now it is time to map the information you want to register per sampling point. This will provide us with an indication of the similarity or differences between sampling points. The information recorded might even differ per product at one and the same sampling point. For instance, some raw materials might require additional testing.

This is valuable input in deciding on how to structure and set up AlisQI.

General information often consists of input like the product name, name of the operator, batch number, machine number and remarks. The analytic values are the values you want measured and registered per sample (i.e. pH or Moisture content).

Tip: Think about information recording with reporting in mind. You can only report the information available in the system. So, all information that you want to use in your charts, reports or filters should be recorded first.

For John’s Bakery the general contents are equal at each sample point, whereas the analytic values differ per point.

We now have a clear map of the sampling points and the information required at each sample point. It is now time to choose the way we set this up in AlisQI.

4. Setting up analysis-sets

Now it is time to think about how to convert the sampling points we have defined into analysis-sets in AlisQI. This is an important question since the manageability and the recognizability of your system are at stake here. In this step we need to decide whether we create:

  • One analysis-set per sample point
  • One analysis-set per product per sample point
  • One analysis-set per product (group) for the whole process or per sampling point
  • Or any other combination

The best setup to choose completely depends on how complicated and diverse your processes are. In order to make the right decision there are some functionalities you need to know about.

4a Need to know

Each mandatory selection list you use in an analysis-set can be set as an Index field. The index field drives the specifications and field visibility.

  • Index field
    An index field is a selection list that has a special meaning in AlisQI. For all options in the index field you can assign individual specifications and vary the field visibility.
    Product selection lists are often used as index fields. This allows you to differentiate specifications and test parameters per product.
  • Specifications
    Specifications can be managed per option of the selection list which is defined as the index field. In the example below you can see that the selection list Product is set as an index field for the analysis-set Final product inspections. This means that the specifications can be inputted per product.
    Example: Product A can have a pH spec ranging from 6 to 7, and Product B can have a pH spec ranging from 7 to 8.

  • Field visibility
    When you have defined an index field in your analysis set, you can vary the visibility of your fields per option of your index field. This enables you to vary the analyses per product.
    Example:  In the screenshot below you can see that for product Acrafix FF all available tests apply. For Asy Novelo however, the Refractive Index, Solids content, Status and Remarks are not applicable. By unchecking their boxes in the Field Visibility, the system knows it should hide these fields when Asy Novelo is selected.

    This enables us to create product specific variations within an analysis-set. This has great value in limiting the number of analysis-sets, and thus requiring less system maintenance.

    In this example we have two products with a rather similar test plan, and thus a limited variation in their field visibility.
    But what if the variety is not so limited? What if different products within the same sampling point are tested on completely different aspects? The more variation there is between products the more effective it might be to separate these products into different analysis-sets.

    Let’s say we have two product groups: Food and Feed. And assume that the products in the Food product group have a completely different set of tests than the products in the Feed product group.

    Since there is so much difference in the test plans between those two groups, we might as well consider them as completely different. Although they both represent a final product inspection. In this case, we would recommend to create distinct analysis-sets for Food and Feed.

    Since the product group Feed still consists of multiple products, we will define the Product selection list as the index field. This allows for product-specific management of field visibility and specifications.

Choose your setup
The setup you choose should be the outcome of the evaluation of your process and its variation per product and sampling point. Ask yourself which analysis-sets you foresee, and whether they should be combined or separated, per sampling point or product(group).

There is no right or wrong. Just give it a try. Nothing is ever set in stone. You can always migrate your data to another setup.

Now let’s get back to John’s Bakery.

4b Creating analysis-sets

As we saw at John’s Bakery the different sampling points have different information and characteristics to be recorded. However, within one sampling point there is not a lot of variety in the values to be recorded, between the various products.

For John’s Bakery one analysis-set per sampling point would suffice. Let’s create the first analysis set: Raw materials. The information we want to record is:

We create a new analysis set via Management » Analysis sets.

We recommend to name the analysis-sets and the analysis-set groups in a way that the users recognize the process and the underlying analysis-sets. After entering the names of the group and of the analysis set we are ready to create the fields required. Click on New field.

We can now select which type of field we wish to create. In this case we select Selection list, we then click on New selection list.

Next we type in the name of the selection list and we put in the names of the different bakers. After clicking Create, a new selection list have been made, this list can easily be selected in every other analysis-set you make.

We want this selection list to be mandatory, so we set Required on Yes, after that we click on Save. One new field has been added.

If you click on Example, you will get an example view of the analysis-set. Here you can also see that the selection list has been added.

We now create the other necessary fields for this analysis-set.

Remember: Specifications can be set per option of the selection list which is defined as the index field.

We want to be able to set specifications for different articles, therefore we select Article as Index field.

Tip: Generally a selection list representing Products / Articles / Items is defined as the index field .
We define a product as: “The entity represented by a unique set of specifications”. From this definition it makes sense that each product has its own specifications, and should thus be defined as the index field

By dragging a field up or down the list you can easily redirect the order of the fields. After clicking on Save the first analysis-set is complete.

The analysis-set is now visible under Drafts, by clicking on Publish the analysis-set will be available for use.

When we go to Results -> Raw materials. Clicking on the name of the analysis-set will direct us to the results overview, the plus symbol will lead us to the result entry.

Field visibility and specifications are now ready to be inserted. Should you however wish to import historical data in AlisQI then it would be better to do this before inserting specifications.

5. Collect historical data & import in AlisQI

To have a good start with AlisQI we recommend importing historical data in AlisQI. That way you won’t need to access this data in your old system anymore and you will get statistical insights on your processes right away.

To see how to import data into AlisQI click here.

6. Insert specifications per analysis-set

After the analysis-set is filled with data it is time to insert specifications.

If you wish to set specifications per product or other selection list options, then that selection list needs to be set as index field. If no index field is set then you can only set a specification for the whole analysis-set, in that case all results will be matched against the same specifications.

To add specifications, we go to Results -> Specifications.

We then click on the just created analysis-set, where we see the raw materials we just inserted via a selection list

We now click on Enter specification version and we insert the necessary specifications.

If you already imported historical data into the analysis-set then think about the start date of the specification. The start date and time will automatically be set at this moment. If historical data should be matched against the specifications then the start date (and time) should be changed.

In case of John’s Bakery we have the following outcome.

We see that the imported results have already been tested against the given specifications. Even better: since we have defined the Article as the index field, all samples have been tested against the specification of their specific article.

Now that there are results in the analysis-set, a whole new playground is available in AlisQI, especially concerning statistics. Take a look here to see what you can do with these results.

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