The authors in this study talk about the current and future changes in the field of quality engineering (Vining et al., 2015). In manufacturing, engineers are concerned most about the efficiency of processes and methods used to enhance performances. In the past decades, individuals identified statistical approaches used to improve productivity excellence in any engineering system. The authors start by first providing an overview of significant advances and trends that have taken place in the past decades and inform further how engineering should evolve to make new contributions.
The article is majorly a reflection on where quality engineering is headed in light of the current situation associated with manufacturing. According to the authors, the field is transforming from the past challenges. Initially, individuals perceived quality engineering as the concept for improving the value of products, services, productivity, or reliability in the manufacturing sector. Individuals in the field contributed to such notion through the existence of agencies such as the American society for quality engineer certification (ASQ) (Vining et al., 2015).
On the contrary, contemporary issues need adaptation to key basic tools in the industry, and the future depends on how well the equipment is embraced. In the coming days, it is perceived that robotic systems will control the manufacturing environment to enhance productivity. Economic and high-tech sensors for data collection will obtain valuable information to improve outcomes of the products. Such changes will result in sophisticated operations and a series of more complicated processes. Consequently, research methodologies will be required to meet the industry demand.
The future of quality engineering is deemed to have brighter changes, and it will also contain significant challenges. According to the authors, one issue that will face the profession is an increased divide between practitioners and academic research needs (Vining et al., 2015). Professionals need to focus on the problems in the real world to meet the demand for new applications. The study mentions recent advances such as the extension of standard methodologies for addressing issues, experimental designs, profile monitoring, computer experiments, statistical approach, and software advances. While current software can perform complex statistical analysis, there are new capabilities such as computer experiments modeling with new systems features.
Future directions will involve integrating quality engineering concepts into systems, using massive data sets, image data, experimenting with functional profiles, and focusing on reliability and statistical engineering. Traditional designs and analysis of systems played a crucial role in the innovation and creation of products that customers could never imagine. Introduced changes in the manufacturing field have brought quality engineering to the focus on creativity.
While changes in the systems have taken place, what has facilitated more growth is practitioners’ training. The authors argue that software development or changes sometimes exacerbate problems because they do not recognize when users are misapplying statistical methods (Vining et al., 2015). With that, follow up training tend to counter errors.
The quality engineering field has to evolve for survival, and experts in the field must look at the productive path forward. With changes taking place in the industry, opportunities for significant contributions prevail. Quality engineers combine the appreciation of process thinking and knowledge of variability to handle emerging problems. Experts and practitioners in the field must seize opportunities and adapt steadily.
Reference
Vining, G., Kulahci, M., & Pedersen, S. (2015). Recent advances and future directions for quality engineering. Quality and Reliability Engineering International, 32(3), 863-875. Web.