Traceability is typically considered crucial only for sectors such as food, automobiles, or aircraft, where products might be recalled very easily. With time, it became clear that every manufacturing industry should have implemented Product Traceability processes in order to increase the quality of end products.
With intelligent product traceability modules, every failure of the production chain can be easily detected and so quickly withdraw faulted batches of products. That is exactly the whole point of a traceability system: connecting the physical flow of goods with the flow of information and ensuring complete documentation of all stages of the supply chain and production.
Jabil faced a problem with Product Traceability and legacy system performance. Company needed to build a solution that will track every part of the product throughout the manufacturing process, from the moment when raw materials enter the factory to the moment when final products are shipped.
Meet Our Client
Jabil’s services include design engineering, manufacturing, supply chain services for the EMS and consumer industries; and materials technology services (plastics, metals, automation, and tooling).
The portfolio of its clients consists of reps from numerous industries, including healthcare, life sciences, clean technology, instrumentation, defense, aerospace, automotive, computing, storage, consumer products, networking, and telecommunications.
Case Study Shortcut
Challenge
Lack of End-to-End Visibility in Manufacturing
Jabil struggled to trace components and materials throughout the entire production lifecycle – from raw material intake to final product shipment. This made it difficult to detect defects early or isolate faulty batches, leading to potential quality and compliance risks.
Inability to Quickly Respond to Quality Issues or Recalls
Without intelligent traceability, identifying the source of a fault and initiating a product recall was time-consuming and prone to errors. This delayed corrective action, risking reputational damage and increasing operational costs.
Goal
Company was looking for a partner able to design and implement the product traceability system to increase security and safety throughout the whole production chain and to set an agreeable model for raw material supply.
- Increase quality and safety
- Improve product recalls
- Improve inventory tracking
- Improve customer service
Outcome
The developed application demonstrates how AI solutions for the manufacturing industry can improve quality and operational efficiency by providing manufacturers with real-time visibility into production processes and facilitating faster root-cause analysis.
The manufacturing traceability solution helps identify critical points where additional quality checks should be introduced. It enables the company to quickly investigate production-related issues while increasing transparency and accountability across the supply chain.
Traceability supported by direct part marking creates a documented record of each product, including its history, components, quality, and safety data. This makes it easier to verify that products meet defined standards and comply with relevant industry regulations.
Before
- Challenging Operation Transparency
- Slow and demanding Data Analysis Processes throughout Supply Chain
- Data Closed in Silos
After
- Improving Operation Transparency
- Increasing Customer Confidence
- Ensuring Product Quality
- Facilitating Root-cause Analysis
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Case Study Details
Approach
Implementation of a Data Lake (AWS-Based)
- Designed to ingest and store massive volumes of data efficiently.
- Stored as flat files to optimize for cost-effectiveness and scalability.
Deployment of a Data Processing Engine
- Processes data ingested into the Data Lake.
- Validates data quality to ensure accurate reporting.
- Prepares data for fast and structured access in the reporting phase.
Development of a Reporting Layer
- Built to enable fast, standard product traceability reports across the manufacturing lifecycle.
- Supports high-performance access to structured information for daily operations.
Implementation of an Ad-Hoc Reporting Tool
- Allows end-users to perform self-service data exploration.
- Enables discovery of relationships between products, components, suppliers, and customers.
- Supports quick querying of large datasets for faster insights and decision-making.
Technology
AWS Glue
Our team
Piotr Danielczyk
Senior Data Engineer
Our Team Expert Opinion
We have started the project with a mutual solution design with the customer. Our goal was to clearly define system features, components, and infrastructure so we ensure that the development process is going smoothly. Later we delivered solutions in desired timelines and using modern approaches like serverless, IaaC, and other modern Data Engineering technologies.
Edwin Lisowski CSO and Co-founder – Addepto
