Quality Improvement In Industry Research Articles

Efficiency of BRICS countries in sustainable development: a comparative data envelopment analysis

Purpose This study aims to assess the efficiency of Brazil, Russia, India, China, South Africa (BRICS) countries in achieving sustainable development by analyzing their ability to convert resources and technological innovations into sustainable outcomes. Design/methodology/approach Using data envelopment analysis (DEA), the study evaluates the economic, environmental and social efficiency of BRICS countries over the period 2010–2018. It ranks these countries based on their sustainable development performance and compares them to the period 2000–2007. Findings The study reveals varied efficiency levels among BRICS countries. Russia and South Africa lead in certain sustainable development aspects. South Africa excels in environmental sustainability, whereas Brazil is efficient in resource utilization for sustainable growth. China and India, despite economic growth, face challenges such as pollution and lower quality of life. Research limitations/implications The study’s findings are constrained by the DEA methodology and the selection of variables. It highlights the need for more nuanced research incorporating recent global events such as the COVID-19 pandemic and geopolitical shifts. Practical implications Insights from this study can inform targeted and effective sustainability strategies in BRICS nations, focusing on areas such as industrial quality improvement, employment conditions and environmental policies. Social implications The study underscores the importance of balancing economic growth with social and environmental considerations, highlighting the need for policies addressing inequality, poverty and environmental degradation. Originality/value This research provides a unique comparative analysis of BRICS countries’ sustainable development efficiency, challenging conventional perceptions and offering a new perspective on their progress.

Insights into the effects of ISO 9001:2015 on quality and process improvement in the South African packaging industry: A leadership perspective

Insights into the effects of ISO 9001:2015 on quality and process improvement in the South African packaging industry: A leadership perspective

Statistical process control and PDCA for quality improvement in the mexican automotive industry

Despite the advancements witnessed in the realm of quality improvement, Statistical Process Control (SPC) perseveres as a universally embraced and extensively employed tool within manufacturing companies across the globe. This enduring popularity can be attributed to its adherence to the time-tested principles established by Shewhart, which have withstood the test of time since their inception in 1924. Over the years, SPC has consistently proven its efficacy in optimizing manufacturing processes, enhancing product quality, and fostering continuous improvement initiatives. Quality is an utmost necessity in the automotive industry, which ranks as the 3rd most significant industry in Mexico and the 5th globally in terms of volume and transactional activity. This research focuses on a successful real case study that demonstrates the enhancement of capability in a critical machining operation within an automotive plant located in Mexico, specifically dedicated to truck engine remanufacturing. This improvement was achieved through the analysis of x̅ and R control charts, followed by the implementation of the Plan-Do-Check-Act (PDCA) cycle. The results obtained were derived from a comparative analysis of data from two distinct time periods in the machining process of bushing diameters. This analysis revealed a significant increase in process capacity, with a 13.08% improvement in the Process Capability Index (Cpk) and a 17.2% enhancement in the Process Performance Index (Ppk). The decrease in expected out-of-specification parts showed a remarkable improvement of 72.7%. Additionally, there was an enhancement in process variability, with a notable 8.33% reduction in the mean range. The significance of this research lies in its empirical identification of gaps and opportunities within the realms of quality assurance and quality control, utilizing methodologies for quality improvement. By uncovering these gaps and opportunities, this study provides valuable insights that can guide future efforts to enhance quality practices and drive continuous improvement in the field.

Research on the efficiency evaluation of the integration of technology and finance in China's strategic emerging industries.

The combination of technology and finance has a great potential impact on regional social and economic development, and strategic emerging industries are the convergence of technological innovation and financial support, the development of which have great significance for industrial structure adjustment and industrial quality improvement. The geographical distribution of emerging strategic industries in China is uneven. We selected 18 provinces with relatively concentrated emerging industries. 206 STI board enterprises in 2020 were collected. A three-stage DEA model was used to measure the input-output efficiency of the integrated development of science and technology finance. Also, we used a regression model to examine the path of integrated development of science and technology innovation and financial support. The research finds that the development of strategic emerging industries has a large demand for financial support and obvious regional differences, and the government plays a strong guiding role in their development as well. At the end of the research, countermeasures and suggestions for the development of strategic emerging industries are given.

Analytical modeling of quality parameters in casting process – learning-based approach

PurposeFoundry produces cast metal components and parts for various industries and drives manufacturing excellence all over the world. Assuring quality of these components and parts is vital for the end product quality. The complexity in foundry operations increases with the complexity in designs, patterns and geometry and the quality parameters of the casting processes need to be monitored, evaluated and controlled to achieve expected quality levels.Design/methodology/approachThe literature addresses quality improvement in foundry industry primarily focusing on surface roughness, mechanical properties, dimensional accuracy and defects in the cast parts and components which are often affected by numerous process variables. Primary data are collected from the experts working in sand and investment casting processes. The authors perform machine learning analysis of the data to model the quality parameters with appropriate process variables. Further, cluster analysis using k-means clustering method is performed to develop clusters of correlated process variables for sand and investment casting processes.FindingsThe authors identified primary process variables determining each quality parameter using machine learning approach. Quality parameters such as surface roughness, defects, mechanical properties and dimensional accuracy are represented by the identified sand-casting process variables accurately up to 83%, 83%, 100% and 83% and are represented by the identified investment-casting process variables accurately up to 100%, 67%, 67% and 100% respectively. Moreover, the prioritization of process variables in influencing the quality parameters is established which further helps the practitioners to monitor and control them within acceptable levels. Further the clusters of process variables help in analyzing their combined effect on quality parameters of casting products.Originality/valueThis study identified potential process variables and collected data from experts, researchers and practitioners on the effect of these on the quality aspects of cast products. While most of the previous studies focus on a very limited process variables for enhancing the quality characteristics of cast parts and components, this study represents each quality parameter as the function of influencing process variables which will enable the quality managers in Indian foundries to maintain capability and stability of casting processes. The models hence developed for both sand and investment casting for each quality parameter are validated with real life applications. Such studies are scarcely reported in the literature.

Non-destructive quality assessment method for Korla fragrant pears based on electrical properties and adaptive neural-fuzzy inference system

This study aimed to achieve the rapid and non-destructive quality assessment of Korla fragrant pears, thereby maximising the value of damaged pears and improving the market supply–demand balance. The electrical characteristics of damaged Korla fragrant pears were measured using a fruit electrical property detector and the trends in the quality of the fragrant pears within their shelf life were analysed. The quality of damaged Korla fragrant pears was predicted by using an adaptive neural-fuzzy inference system (ANFIS). Electrical properties were used as inputs to the system and quality was the output of the system. A total of eight functional models with different degrees of membership were constructed and the optimal one was selected. The results demonstrated that the equivalent parallel capacitance (Cp) of the damaged Korla fragrant pears increased gradually throughout their shelf life, while equivalent parallel resistance (Rp) and complex impedance (Z) decreased. Additionally, the green–red difference (a*) increased gradually, while hardness and soluble solid content (SSC) decreased continuously. Based on the combination of electrical properties and the ANFIS, gbellmf was the optimal model to determine the SSC of the damaged Korla fragrant pears (R2 = 0.9123) and gaussmf was the optimal model to determine the hardness and a* of the damaged Korla fragrant pears (R2 = 0.9112 and 0.8853, respectively). It was concluded that the combined use of electrical properties and the ANFIS method enabled the successful quality assessment of fragrant pears. This approach was conducive to facilitating the optimisation and updating of non-destructive quality assessment technologies for fragrant pears, promoting quality and efficiency improvement in the fragrant pear industry.

Classification of Industrial Heat Source Objects Based on Active Fire Point Density Segmentation and Spatial Topological Correlation Analysis in the Beijing–Tianjin–Hebei Region

The development of industrial infrastructure in the Beijing–Tianjin–Hebei(BTH) region has been accompanied by a disorderly expansion of industrial zones and other inappropriate development. Accurate industrial heat source classification data become important to evaluate the policies of industrial restructuring and air quality improvement. In this study, a new classification of industrial heat source objects model based on active fire point density segmentation and spatial topological correlation analysis in the BTH Region was proposed. First, industrial heat source objects were detected with an active fire point density segmentation method using NPP-VIIRS active fire/hotspot data. Then, industrial heat source objects were classified into five categories based on a spatial topological correlation analysis method using POI data. Then, identification and classification results were manually validated based on Google Earth imagery. Finally, we evaluated the factors influencing the number of industrial heat sources based on an OLS regression model. A total of 493 industrial heat source objects were identified in this study with an identification accuracy of 96.14%(474/493). Compared with results for nighttime fires, the number of industrial heat source objects that were identified was higher, and the spatial coverage was greater; the minimum size of the detected objects was also smaller. Based on the function of the identified industrial heat source objects, the objects in the BTH region were then divided into five categories: cement plants (21.73%), steel plants (53.80%), coal and chemical industry (12.66%), oil and gas developments (7.81%), and other (4.01%). An analysis of their operations showed that the number of industrial heat source objects in operation in the BTH region tended to first rise and then decline during the 2012–2021 period, with the peak being reached in 2013. The results of this study will aid the rationalization of industrial infrastructure in the BTH region and, by extension, in China as a whole.

Industrial agglomeration and product quality improvement of food enterprises: empirical analysis based on data from Chinese enterprises

This study utilized data on dairy enterprises, which are representative of China's food industry, to investigate the relationships and mechanisms between industrial agglomeration and the product quality of food enterprises. The results show that industrial agglomeration significantly improves the product quality of Chinese food enterprises. In general, the economic effect of China's food industry agglomeration is greater than that of excessive competition. The heterogeneity analysis showed that industrial agglomeration plays a more important role in promoting the product quality of non-state-owned enterprises and food enterprises in the eastern region than in state-owned enterprises and the central and western regions. Further mechanistic analysis showed that industrial agglomeration promotes food quality improvement by improving enterprise productivity and fixed cost input efficiency. Therefore, this study confirms that industrial agglomeration can be used as an external driving force for China's food quality improvement. On the basis of market mechanisms, through the guidance of the macro policy of industrial agglomeration, the external economies of the scale effect of agglomeration are of great significance for helping the food industry become high quality and high end.

An integrated SEM-ANN approach for predicting QMS achievements in Industry 4.0

Industry 4.0 brings a revolution in using information and communication technologies within business activities. As such, Industry 4.0 enables important space for quality-related improvements but requires a sustained quality management system (QMS). The aim of this study is to predict the influence of ISO 9004:2018 QMS elements on Improvement, Learning, and Innovation achievements in Industry 4.0 using the SEM-ANN approach. The survey included 345 domestic and international companies of different types operating in Serbia. Conclusions demonstrate a direct positive influence between observed constructs (Leadership, Process Management, Resource Management, Performance Management) and Improvement, Learning, and Innovation. Only the Context and Identity of the organisation has a negative direction drawn from SEM analysis. Further, ANN verified SEM results, pointing out that all observed variables are seen as predictors of Improvement, Learning, and Innovation. The importance level corresponds to those elements’ SEM ranking. The paper could provide a roadmap towards achieving sustainable results in quality improvement, learning, and innovation in Industry 4.0 era.

An Overview on Food Applications of the Instant Controlled Pressure-Drop Technology, an Innovative High Pressure-Short Time Process.

Food processing systematically aims at meeting the needs of consumers who are looking for total high quality and perfect food safety. As the various thermal and non-thermal food preservation technologies often affect the natural properties in terms of sensation, flavor, texture, etc., instant controlled pressure drop (DIC) has been conceived as a relevant, innovative process in this field. DIC uses high saturated steam pressure and short duration to provide a new way to expand biological matrices, improve drying, decontaminate, and extract biologically active compounds, among other attributes. Therefore, this review focuses on describing the applications of DIC technology on a wide range of products such as foods and by-products that have been processed both in the laboratory and on an industrial scale. The application of DIC has shown the possibility of a significant leap in quality improvement and cost reduction in the food industry. DIC reduces the drying time of fruits and vegetables, and improves the extraction of essential oils, vegetable oils, and antioxidant components. It also provides strong decontamination, eliminates vegetative microorganisms and spores, and reduces non-nutritional and allergenic components. Over the past 33 years, this technology has continued to expand its food applications and improve its characteristics on an industrial scale. But there are still many food unit operations that can be taken to the next level with DIC.

Implementation of lean manufacturing with the notion of quality improvement in electronics repair industry

Electronic equipment repair services are one of the fastest-growing businesses that can create millions of jobs. But sensing its untapped potential, investments are flowing in creating a roadmap to improve its capacity to deliver quality products into the market. As far as electronics repair industries are concerned, there are bottlenecks and defects in each process. Moreover, due to the unprecedented crisis of COVID-19 has resulted in losing customers. To overcome these challenges, companies have to work to achieve their objectives other than profit. Industries have to adopt a better quality management system that addresses all industry areas, emphasizes customer satisfaction, and uses continuous improvement methods and tools. Lean manufacturing helps any organization to improve its efficiency, eliminate wastes, and achieve continuous improvements. This paper highlights the implementation of lean and quality tools for continuous improvements in electronic repair industries with no automation. Two levels of the repair bay process were chosen to remove the bottlenecks affecting quality and productivity. The paper sums up that implementing Lean Manufacturing resulted in continuous improvement and facilitated human workers to enhance their repair process quality.

Inclusive Approach for Quality and Safety Environment Improvement in Oil and Gas Industry

Implementing safety behavior in the oil and gas industries is still challenging, although fatal accidents often occur. This research aims to analyze how SHEQ talks, a Badak LNG program, can successfully prevent workers' work accidents. Using qualitative methods with a case study approach, the researchers interviewed several key persons in the SHEQ talk program, including the board of management, the SHEQ department's employees, and Badak LNG's employers. Inclusiveness is the main component in the SHEQ talks program. It leads to safety behavior among all Badak LNG's workers (interdependent stage). Unlike the usual behavior-based safety program, SHEQ talks encourage all employees to have good knowledge and skill of health and safety environments. Therefore, safety performance among the workers does not entirely depend on the OSH officers. Eliminating the superior and subordinate when conducting the safety talks are essential to build the safety culture among workers in the oil and gas industries.

Improving quality in a complex primary care system-An example of refugee care and literature review.

Applying traditional industrial quality improvement (QI) methodologies to primary care is often inappropriate because primary care and its relationship to the healthcare macrosystem has many features of a complex adaptive system (CAS) that is particularly responsive to bottom-up rather than top-down management approaches. We report on a demonstration case study of improvements made in the Family Health Center (FHC) of the JPS Health Network in a refugee patient population that illustrate features of QI in a CAS framework as opposed to a traditional QI approach. We report on changes in health system utilization by new refugee patients of the FHC from 2016 to 2017. We review the literature and summarize relevant theoretical understandings of quality management in complex adaptive systems as it applies to this case example. Applying CAS principles in the FHC, utilization of the Emergency Department and Urgent Care Center by newly arrived refugee patients before their first clinic visit was reduced by more than half (total visits decreased from 31%-14% of the refugee patients). Our review of the literature demonstrates that traditional algorithmic top-down QI processes are most often unsuccessful in improving even a few single-disease metrics, and increases clinician burnout and penalizes clinicians who care for vulnerable patients. Improvement in a CAS occurs when front-line clinicians identify care gaps and are given the flexibility to learn and self-organize to enable new care processes to emerge, which are created from bottom-up leadership that utilize existing interdependencies and interact with the top levels of the organization through intelligent top-down causation. We give examples of early adapters who are better applying the principles of CAS change to their QI efforts. Meaningful improvement in primary care is more likely achieved when the impetus to implement change shifts from top-down to bottom-up.

Quality improvement in readymade garments industry by traffic light system

Consumers, manufacturers, and retailers worldwide are becoming conscious about high quality products at minimum cost. But plenty of apparels are becoming waste which increases the cost of production. As resources are decreasing but increasing costs of the products. Effective apparel waste management is needed to ensure the profit. Reducing such waste can be profitable options for the manufacturers as well as the buyers. Considering this matter, a project work is done in a ready-made garment manufacturing industry to improve the quality of the products through using a traffic light system. A traffic light system was implemented to minimize the defect rates of production. The study shows that the average defect rates were dropped from 4.13 to 1.25 pieces of a line for daily eight hours of production. By implementing this system, the defect rates are minimized and the monthly production is also increased and it clearly depicts that the monthly capacity before implementing the traffic light system was equivalent but the defective production was more whereas, after implementation, the defective production was negligible.

Quality improvement in hospitals' surgery-related processes: A systematic review.

Background: There is a growing global movement toward quality and safety in healthcare and quality improvement (QI) in general surgery. The fundamentals of QI begin with an understanding of the underlying theoretical framework. This study aims to provide an overview of the existing QI models and frameworks for general surgery. Methods: In this systematic review, published literature from January 2007 until September 2018 were retrieved from PubMed, Scopus, Web of Science and Embase databases, and Google Scholar using the MeSH terms related to QI and surgery. In total, 25 fulltext articles were finally included, and data extraction was based on research objectives. Results: Nine models were identified for QI in general surgery. These models were categorized into two main groups: (i) conceptual models or frameworks designed for QI in industry and applied in surgery, and (ii) those designed specifically for QI in surgery. Identified QI models were more used for improving postoperative processes and pre-hospital trauma care, identifying causes of prolonged periods of stay and lowering LOS index, improving surgical antimicrobial prophylaxis and antibiotics administrating during surgery process, reducing and controlling infections, reducing complications, reducing mortality and morbidity, reducing waiting times and start time delays, reducing variability and improving surgical clinic experience, reducing costs, improving operating room efficiency by removing processes that add no value, and lowering per-capita costs. Conclusion: According to the findings of this study, there are different models and frameworks with different aspects and dimensions for QI in surgery, which is recommended to use either of these models alone or with each other for specific circumstances. The use of these models in surgery is increasing, and it is recommended that these models could be used according to their functions in cases such as reducing the unnecessary use of resources, increasing the satisfaction of patients and their families with health care and improving the efficiency, safety and quality of healthcare in the surgical departments.

Ensuring Effectiveness of Industrial Cluster Development

Industries sector needs utilities and logistics support to grow. Ensuring industrial logistics and utilities from one corner of a country to the other is not possible for any new economy like post-liberation war Bangladesh. A dedicated government agency is required to facilitate industrial utilities and logistics for existing and upcoming entrepreneurs of the country. To facilitate industrialisation in the then-East Pakistan, Small and Cottage Industries Corporation Act, 1957 was enacted by the Minister for Labour, Commerce and Industry Bangabandhu Sheikh Mujibur Rahman. He established East Pakistan Small and Cottage Industries Corporation (PSCIC). Following independence, this institute was transformed into Bangladesh Small and Cottage Industries Corporation (BSCIC). Since then, the BSCIC has played a pivotal role in the development of industrial estate in the country. Notable activities of BSCIC are entrepreneurship development through counselling and training; providing infrastructural facilities by establishing industrial estates; extending credit facilities to the entrepreneurs from its own funds and also through banks and financial institutions; preparation of project profile and project appraisal proposal; providing technical and consultancy services for establishing new industrial units and quality improvement of small cottage industry products; registration of small and cottage industrial unit and recommending exemption of duties and taxes for the small industrial raw materials and product etc. Till date, BSCIC has developed around 94 industrial estates around the country. BSCIC industrial estates are the first official forms of industrial clusters in Bangladesh.

Lean Six Sigma Methodology in the Implementation of a Standardized Health Literacy Assessment in a Safety Net Internal Medicine Residency Clinic.

Background:Lean Six Sigma is a set of techniques intended to improve processes by greatly reducing the probability that errors will occur. The Lean Six Sigma approach was used to engage staff and clinicians in standardizing the assessment of patient health literacy in an academic safety net clinic.Brief description of activity:Clinicians were surveyed, and a chart review was conducted to attain baseline information regarding the uniformity of health literacy assessment and documentation in the clinic. A workgroup used the survey data and Lean Six Sigma quality improvement tools to determine the root cause, which was the lack of standardization.Implementation:To address this root cause, a standardized process for health literacy assessment in the clinic was developed; an assessment tool was selected, support staff were trained, and the new process was initiated. A support staff focus group was conducted, and a second clinician survey was disseminated to gauge perception of the new health literacy assessment and documentation processes. Quantitative data were collected to assess the coverage achieved by the new processes. Monthly reporting and staff feedback sessions were conducted to ensure continued efficacy of the protocol.Results:Standardized assessment and documentation processes were effectively implemented using the Lean Six Sigma approach in an academic safety net clinic. Providers and rooming staff were satisfied with the new processes. Rooming staff input and buy-in were critical to successful implementation.Lessons learned:Our findings suggest that Lean Six Sigma tools and methodologies can be appropriate for health care quality improvement and process standardization in an academic safety net clinical setting. [HLRP: Health Literacy Research and Practice. 2019;3(1):e25–e30.]Plain Language Summary:A growing body of evidence supports the role of Lean Six Sigma (LSS) tools and processes for the assessment, design, and implementation of the quality improvement in the health care industry. This study explored the use of LSS on the standardization and documentation of health literacy assessment of patients in an academic safety net clinic. Findings suggest that LSS is an appropriate method of standardizing assessment and documentation of health literacy in this clinical setting.

Patulin biodegradation and quality improvement of apple puree fermented with Byssochlamys nivea FF1-2

Abstract The filamentous fungus Byssochlamys nivea FF1-2 is a recently reported strain with excellent patulin biodegrading capability. This study investigated the effects of FF1-2 on the quality of apple puree during the process of patulin degradation. Apple puree artificially contaminated with high-dose patulin (125, 250 and 500 μg/mL) was fermented by FF1-2 for 10 days, and over 97% of patulin was degraded in the apple purees after fermentation, and the maximal degradation of patulin was 98.5%. Physicochemical analysis demonstrated that after 10 days of fermentation, the pH and the amount of reducing sugars in the apple puree decreased significantly. The volatile profile assessment of fermented apple puree obtained from HS-SPME/GC-MS indicated that the amounts of acids, aldehydes and ketones decreased, and the content of aroma-active compounds mainly aliphatic alcohols and esters, were significantly increased after FF1-2 fermentation. In addition, further reports of sensory evaluation also revealed good acceptability of the fermented apple puree. Thus, FF1-2 not only effectively degraded patulin in apple puree, but improved quality of apple puree, especially the aroma profile. These findings indicate that FF1-2 has a promising application for controlling mycotoxin contamination and quality improvement in juice production industry.

What Hospitalists Need to Know About Quality Improvement

The purpose of this review is to discuss quality improvement in the roles of Hospitalists. Healthcare has seen two parallel evolutions in the field over the last 2 decades; the first being the integration of industrial quality improvement methodologies into healthcare with the aim of reducing cost and improving quality of care. At the same time, the inpatient care model has shifted with the development and significant growth of the hospitalist profession. Hospitalists are physicians dedicating their sole practice to the care of hospitalized patients, and merging this knowledge with that of quality improvement methodologies can provide a platform to improve the quality of care delivered to hospitalized patients.

Comparison Between the Economic-Statistical Design of Double and Triple Sampling X¯\bar{X} Control Charts

Abstract Control charts have been established as major tools for quality control and improvement in industry. Therefore, it is always required to consider an appropriate design of a control chart from an economical point of view before using the chart. The economic design of a control chart refers to the determination of three optimal control chart parameters: sample size, the sampling interval, and the control limits coefficient. In this article, the double sampling (DS) X ¯ {\bar{X}} control chart is considered for the economic design using nonlinear mixed integer programming approach. The triple sampling (TS) X ¯ {\bar{X}} control charts are developed for economic design based on the results of solving the DS X ¯ {\bar{X}} chart design problems. In this model, we assume that the process must be shut down during the search for the assignable cause. Multiple sampling X ¯ {\bar{X}} charts can be designed for quick detection of a small shift in process. The results of the comparison between the economic-statistical design of DS and TS X ¯ {\bar{X}} control charts show that TS X ¯ {\bar{X}} control charts are more efficient in terms of minimizing the average sample size, but its expected average cost takes larger values.