To support the dynamic needs of our customers, GMN Plastics adheres to stringent quality principles to ensure that products meet the required specifications. Our robust quality services and core tools help to reduce scrap rates and costs and continuously improve our manufacturing processes.
First article inspection
GMN Plastics performs First Article Inspection (FAI) reporting for every new or revised part and assembly, big or small. As a detailed design verification process, it validates our ability to manufacture products in accordance with the customer specifications, resulting in reduced manufacturing delays and defects.
GMN Plastics utilizes SOLIDWORKS® Inspection to automate the First Article Inspection process. Equipped with optical character recognition to digitally measure and document data, this advanced software is less prone to human errors and ensures that your product reaches the market faster. With access to Net-Inspect, the online global supplier portal, we can also create AS9102 FAI reports that specifically meet the needs of the aerospace industry.
In an effort to optimize output, GMN Plastics conducts design of experiments (DOE) studies to evaluate the influence of individual input parameters on the final product. Depending on the complexity of the design, we perform multi-factor DOE analysis to examine the interaction between different variables in the manufacturing process and quality. In addition, our process capability and stability studies enable our engineers to verify that the production process is consistent, repeatable, and capable of meeting customer specifications.
Quality core tools
The quality core tools, developed by the Automotive Industry Action Group (AIAG), are the very foundation of a sound quality management system. GMN Plastics has adopted these tools to effectively manufacture plastic parts that meet the most demanding customer needs. For any given project, the five core tools utilized are:
- Advanced Product Quality Planning - As a roadmap to effective project management, Advanced Product Quality Planning (APQP) allows GMN Plastics to translate our customer needs into defined goals, specifications, and time-based milestones. From quotation to the final shipment of parts, this structured tool identifies every step in the design and production planning process to deliver high-quality products to our customers in a timely manner.
- Production Part Approval Process - Plugged into customer requirements, Production Part Approval Process (PPAP) outlines the entire production process flowchart including material sourcing, resource allocation, and logistics. Significantly overlapping with first article inspection, it equips our engineers with a control plan to meet the deliverables mapped out in the APQP.
- Failure Modes and Effects Analysis – The Failure Modes and Effects Analysis (FMEA) tool empowers our quality experts to identify potential gaps in the manufacturing system and establish appropriate control processes to address them. By investigating risks at a micro level, this tool prompts us to preemptively eliminate production bottlenecks and ensure seamless manufacturing.
- Statistical Process Control - Statistical Process Control (SPC) uses statistical data to verify that input parameters are within agreed upon tolerances and to flag an out-of-control situation in the qualification process. It is fundamental to understanding our machine and process capabilities and identifying unwanted discrepancies, ultimately resulting in reduced scrap, rework costs, and rejects.
- Measurement System Analysis - Measurement System Analysis (MSA) uses gage repeatability and reproducibility mathematical processes to measure the inherent variation of a measurement system, analyze the root cause of variations, and ensure that process variations are within the required tolerance limits. It verifies that measurement equipment is calibrated, qualified, and that the system is robust enough to accommodate human and part variation.
In addition to employing the five quality core tools, GMN Plastics also performs in-process statistical analysis to identify and address unacceptable variations and deviations in the production environment. Various statistical tools including capability indices, variable and attribute control charts, and predictive modeling, provide reliable data to our process engineers to monitor developments in production and proactively take corrective measures as necessary.