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Project: Evaluate a Manufacturing Process
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    Manufacturing processes for any product is like putting together a puzzle. Products are pieced together step by step, and keeping a close eye on the process is important.

    For this project, you're supporting a team that wants to improve how they monitor and control a manufacturing process. The goal is to implement a more methodical approach known as statistical process control (SPC). SPC is an established strategy that uses data to determine whether the process works well. Processes are only adjusted if measurements fall outside of an acceptable range.

    This acceptable range is defined by an upper control limit (UCL) and a lower control limit (LCL), the formulas for which are:

    The UCL defines the highest acceptable height for the parts, while the LCL defines the lowest acceptable height for the parts. Ideally, parts should fall between the two limits.

    Using SQL window functions and nested queries, you'll analyze historical manufacturing data to define this acceptable range and identify any points in the process that fall outside of the range and therefore require adjustments. This will ensure a smooth running manufacturing process consistently making high-quality products.

    The data

    The data is available in the manufacturing_parts table which has the following fields:

    • item_no: the item number
    • length: the length of the item made
    • width: the width of the item made
    • height: the height of the item made
    • operator: the operating machine
    Unknown integration
    DataFrameavailable as
    alerts
    variable
    WITH first_query AS (
        SELECT 
            operator, 
            ROW_NUMBER() OVER (PARTITION BY operator ORDER BY item_no) AS row_number,
            height,
            AVG(height) OVER (ORDER BY item_no ROWS BETWEEN 4 PRECEDING AND CURRENT ROW) AS avg_height, 
            STDDEV(height) OVER (ORDER BY item_no ROWS BETWEEN 4 PRECEDING AND CURRENT ROW) AS stddev_height
        FROM 
            manufacturing_parts
        GROUP BY 
            operator, item_no, height
    ),
    
    second_query AS (
        SELECT 
            first_query.*,
            (avg_height + 3 * (stddev_height / SQRT(5))) AS ucl,
            (avg_height - 3 * (stddev_height / SQRT(5))) AS lcl
        FROM 
            first_query
    )
    
    SELECT 
        second_query.*,
        CASE
            WHEN height NOT BETWEEN lcl AND ucl THEN TRUE
            ELSE FALSE
        END AS alert
    FROM 
        second_query
    WHERE 
        row_number >= 5;
    
    This query is taking long to finish...Consider adding a LIMIT clause or switching to Query mode to preview the result.