The cost of poor quality is at the forefront of every plant manager's mind. While the direct costs of producing defective components are relatively easy to quantify, such as scrap, rework, and recalls; the indirect costs can significantly impact a company's profitability, such as increased audits, lost sales, and declining brand reputation. As a consequence, the majority of a manufacturer's time and resources are spent tightening tolerances, ensuring compliance, and/or increasing post-process destructive and non-destructive testing. While such efforts are important to a quality-assured and quality-controlled process, there are diminishing returns for higher standards through increased destructive and non-destructive testing. In most manufacturing environments, the process itself is treated as a black box, where the inputs are tightly controlled and the resulting product is thoroughly tested but the in-process behavior is largely overlooked.
Variability and uncertainty will always exist at some level in a manufacturing process. As a result, many manufacturers devote more time and resources to tightening tolerances, ensuring QA/QC compliance, and increasing post-process destructive and non-destructive testing, yet very little time is spent understanding the relationship between the in-process physical behaviors and the repeatability and quality of the manufacturing process itself. Recently, manufacturers are realizing that their manufacturing processes are data-rich environments that have gone largely untapped. This article reviews a recent research paper that characterizes the inherent variability of an inertia friction welding machine tool and illustrates the importance of real-time, in-process monitoring.
This article presents a historical perspective of the research that fueled the initial development of in-process monitoring for real-time feedback of welding and joining process quality.
The traditional approach to manufacturing quality assurance involves the following activities: (1) control materials, (2) write specifications, (3) train operators, (4) maintain equipment, (5) set and control knob settings, and (6) check part quality through exhaustive final inspection and occasional metallurgical cutups. In the traditional approach, the manufacturing process itself is assumed to be repeatable. Directly monitoring the real-time response of the machine tool or the manufacturing process is not considered.
The goal of an in-process monitoring solution is to measure the process's performance, the product's quality, or both in a real- or near-real-time manner. An in-process monitoring solution should not be regarded as a replacement for post-process, non-destructive examination. Although this can sometimes occur, an in-process monitoring solution can significantly reduce the over-reliance on post-process inspection by transforming it into a value-added step in the manufacturing effort.