Production Cost Dashboards for MSA Safety

Summary

Two Power BI dashboards were created to help compare data, generate reports, and monitor KPIs. The first dashboard monitors scrap costs, and the second shows variations in production costs.

2023

Date

Data Analytics

Safety First

Established in 1914, MSA Safety Incorporated is the world leader in the development, manufacture, and supply of safety products that protect people and infrastructures from hazardous or potentially life-threatening situations.

MSA’s main products include self-contained breathing apparatus, flame and gas detection systems, industrial head protection products, and fall protection devices.

MSA Safety Mexico

MSA Mexico is a subsidiary that manufactures and distributes various safety products, and like any manufacturing company, there are variations in production costs for various reasons: scrap costs, rework, or savings in production processes.

Currently, variations in production costs are reported weekly by email using Excel files, which has several limitations.

Problem

Solution

Workflow

The development of this project was divided into 5 phases:

Ask

Business Task was defined in this phase, as well as a series of questions that guided the dashboard design.

Show Guiding Questions

What is the purpose of creating these dashboards?
- What information needs to be displayed in the dashboards? What doesn’t?
- What is the outcome that stakeholders expect from this project?
What charts will I use in the dashboard? Why?
How can I improve the readability of the dashboard?
- What will be the layout?
- What theme will be used (dark/light)?

Business Task

Create two dashboards in Power BI to visualize and analyze production costs. The first one will display cost variations by work area. The second one will display scrap costs from 2019 to 2023.

Prepare

Data sources were defined, their credibility was confirmed, and issues accessibility were identified.

Where is the data stored?

The data is stored on the company’s servers and in SAP.

How was the data collected?

These datasets were generated and exported from SAP to Excel on a weekly basis (from 2019 to 2023).

How is the data organized?

It is organized in long format.

It includes data on material, work area, date, variation type, amount (currency), and other details. It is saved in XLSX format.

Are there issues with credibility in this data?

There are no issues regarding credibility since these datasets were generated in SAP, and then exported to Excel.

How am I addressing licensing, privacy, security, and accessibility?

Since this data is confidential, it will need to be altered and censored before showing the results.

Processing

The working tools were defined.

The data sets were organized and cleaned (using Excel).
Dasboards were created in Power BI.

Show Process in Detail

Before starting the analysis, I had to check the integrity and consistency of the data. I looked for duplicate values, null values, and made sure all fields had the same format. To do this, I used Excel.

Scrap cost data was compiled into a single Excel file (from 2019 to 2023).
Weekly production cost variation data was compiled into annual Excel files (2022 and 2023).

After this, I imported and transformed the data in Power BI to start creating the dashboards.

Analysis

Data was imported into Power BI and dashboards were created, focusing on readability.

Results are explained in detail in the following section, “Dashboards”.

Feedback

Feedback was received from my supervisor. Changes were made to the colors used, as well as the addition of some metrics such as average lines and labels to show more detailed information in the bar charts.

To avoid redundancy in the presentation of this project, preliminary results were omitted, and only the final results were shown.

Dashboards

According to Bach B. et al. (2022), a dashboard should not overwhelm users, avoid visual clutter, carefully choose KPIs, and not display too much data, among other recommendations.

With this in mind, I started to design the first dashboard.

This dashboard helps visualize scrap costs and compare them with other years to analyze the factory’s overall performance.

Key elements:

A stacked bar chart displays a comparison of costs between selected years.
A KPI card shows the percentage of scrap cost compared to the previous year using DAX functions.
A pie chart displays the total cost comparison between selected years.
A table shows in detail the cost of scrap per year.
A card shows the total scrap cost during the selected interval.

This dashboard is used to display variations in production costs (both savings and losses) by work area, and prioritize strategies to reduce loss-related variations.

Key elements:

You can select any work area and display its production cost variations during the year in the line chart. Also, you can compare this with any other work area.
Two cards display the work area with the highest loss and savings (respectively) using filters.
Two pie charts display a comparison of the work areas with the highest losses and savings (respectively).

Outcomes

Dashboards can now be shared through the cloud and the company’s servers, allowing for more dynamic content updates.

Now production cost variations can be compared not only with other years but also between production lines. This allows for organizing strategies to reduce waste and rework costs in the production lines that need it the most.

Acknowledgment

I would like to thank my supervisor, Eng. J. Rodriguez, for guiding me and answering all my questions throughout the development of this project. I will always carry his teachings and recommendations with me.

References

Show References

Bach, B., Freeman, E., Abdul-Rahman, A., Turkay, C., Khan, S., Fan, Y., & Chen, M. (2022). Dashboard Design Patterns. IEEE Transactions on Visualization and Computer Graphics, 1–11. https://doi.org/10.1109/tvcg.2022.3209448

Tagged Dashboard, Data Analytics, Internship, KPI, MSA Safety, Power BI