The Implementation of Maintenance Quality Function Deployment (MQFD) to Improve the Quality Maintenance Management for the Upstream Oil and Gas Industry

The global energy market is still dominated by oil and gas energy. Pipeline is one of the most efficient means of distributing crude oil. In an oil and gas production unit, pipes are a means that often fails. A pipeline will operate optimally if it gets good maintenance. The concept of Total Productive Maintenance (TPM is an implementation subject that includes the concept of quality improvement engineering, or commonly known as TQM), but in its application, TPM eliminates one of the strategies in TQM, which reflects the voice of the operator (user’s voice) to influence quality improvement ongoing maintenance, so as to perfect the TPM approach, a supporting technique is needed that can reflect the operator’s voice, namely QFD, so that the combination of the two methods or so-called Maintenance Quality Function Deployment (MQFD) models is considered to be able to improve the quality of maintenance because it is a more comprehensive approach, and involves all elements involved, so that the expected quality improvement can be in accordance with the rules of total quality management Based on the results of the TPM parameter calculation, it is known that all OEE values have met the world’s standard of 86%. in carrying out its operations there are still reports of damage, leakage, and vandalism in the production pipeline. Based on the results of the identification of user’s voice, there are 19 attributes of maintenance quality that must be prioritized.

Case Report: Behavioral Unresponsiveness in Acute COVID-19 Patients: The Utility of the Motor Behavior Tool-Revised and 18F-FDG PET/CT

Along with the propagation of COVID-19, emerging evidence reveals significant neurological manifestations in severely infected COVID-19 patients. Among these patients admitted to the intensive care unit (ICU), behavioral unresponsiveness may occur frequently, yet, there are still only a few cases reported and with rare descriptions of their motor behavior after pathological awakening. Several hypotheses regarding central lesions in these patients are conceivable. Here, we describe two acute SARS-CoV-2- infected patients who developed neurological symptoms evoking the condition of clinical cognitive motor dissociation (CMD). This diagnosis could be confirmed first by clinical observation of a dissociation between preserved cognitive abilities and lack of initial motor interaction and second, by performing ¹⁸F- FDG PET imaging. Accurate diagnosis led to an appropriate neuro-rehabilitation regimen with long-term neuro-rehabilitation leading to an improved outcome for both patients.

Transplantation of mesenchymal stem cells for spinal cord injury: a systematic review and network meta-analysis

Spinal cord injury (SCI) is a severe traumatic disease of the central nervous system, with a global prevalence of 236–4187 per million people. This meta-analysis aimed to evaluate the safety and efficacy of mesenchymal stem cells (MSCs) in treating patients with SCI as well as the optimal source and transplantation method of MSCs. PubMed, OVID, Cochrane, Web of Science, and China Biomedical Database were searched up until April 01, 2021. The study was conducted for five endpoints: American Spinal Injury Association (ASIA) motor and sensory score, ASIA grade improvement, Barthel Index (BI), and adverse reactions. Standard meta-analysis and network meta-analysis were performed using Stata 14.0. Eighteen studies with a total of 949 patients, were included in the meta-analysis. Standard meta-analysis showed that MSCs significantly improved ASIA motor score (P < 0.001), sensory score (P < 0.001), ASIA grade (P < 0.001), and BI (P < 0.001) compared to rehabilitation. In addition, in the network meta-analysis, autologous MSCs significantly improved the ASIA motor [MD = 8.01, 95% CI (4.27, 11.76)], sensory score [MD = 17.98, 95% CI (10.04, 25.91)], and BI [MD = 7.69, 95% CI (2.10, 13.29)] compared to rehabilitation. Similarly, compared to rehabilitation, intrathecal injection (IT) of MSCs significantly improved the ASIA motor [MD = 7.97, 95% CI (4.40, 11.53)] and sensory score [MD = 19.60, 95% CI (9.74, 29.46)]. Compared to rehabilitation, however, only the IL of MSCs was associated with more adverse reactions [OR = 17.82, 95% CI (2.48, 128.22)]. According to the results of SUCRA, both autologous MSCs and IT transplantation approaches most improved the neurological function in SCI patients. Cell transplantation using MSCs is effective in patients with SCI and IT of autologous MSCs may be more beneficial.

Mixed-Mode Interlaminar Fracture Toughness of Glass and Carbon Fibre Powder Epoxy Composites-For Design of Wind and Tidal Turbine Blades

Powder epoxy composites have several advantages for the processing of large composite structures, including low exotherm, viscosity and material cost, as well as the ability to carry out separate melting and curing operations. This work studies the mode I and mixed-mode toughness, as well as the in-plane mechanical properties of unidirectional stitched glass and carbon fibre reinforced powder epoxy composites. The interlaminar fracture toughness is studied in pure mode I by performing Double Cantilever Beam tests and at 25% mode II, 50% mode II and 75% mode II by performing Mixed Mode Bending testing according to the ASTM D5528-13 test standard. The tensile and compressive properties are comparable to that of standard epoxy composites but both the mode I and mixed-mode toughness are shown to be significantly higher than that of other epoxy composites, even when comparing to toughened epoxies. The mixed-mode critical strain energy release rate as a function of the delamination mode ratio is also provided. This paper highlights the potential for powder epoxy composites in the manufacturing of structures where there is a risk of delamination.

Elucidating the Neuropathologic Mechanisms of SARS-CoV-2 Infection

The current pandemic caused by the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a public health emergency. To date, March 1, 2021, coronavirus disease 2019 (COVID-19) has caused about 114 million accumulated cases and 2.53 million deaths worldwide. Previous pieces of evidence suggest that SARS-CoV-2 may affect the central nervous system (CNS) and cause neurological symptoms in COVID-19 patients. It is also known that angiotensin-converting enzyme-2 (ACE2), the primary receptor for SARS-CoV-2 infection, is expressed in different brain areas and cell types. Thus, it is hypothesized that infection by this virus could generate or exacerbate neuropathological alterations. However, the molecular mechanisms that link COVID-19 disease and nerve damage are unclear. In this review, we describe the routes of SARS-CoV-2 invasion into the central nervous system. We also analyze the neuropathologic mechanisms underlying this viral infection, and their potential relationship with the neurological manifestations described in patients with COVID-19, and the appearance or exacerbation of some neurodegenerative diseases.

Thrombocytopenia and Intracranial Venous Sinus Thrombosis after "COVID-19 Vaccine AstraZeneca" Exposure

Background: As of 8 April 2021, a total of 2.9 million people have died with or from the coronavirus infection causing COVID-19 (Corona Virus Disease 2019). On 29 January 2021, the European Medicines Agency (EMA) approved a COVID-19 vaccine developed by Oxford University and AstraZeneca (AZD1222, ChAdOx1 nCoV-19, COVID-19 vaccine AstraZeneca, Vaxzevria, Covishield). While the vaccine prevents severe course of and death from COVID-19, the observation of pulmonary, abdominal, and intracranial venous thromboembolic events has raised concerns. Objective: To describe the clinical manifestations and the concerning management of patients with cranial venous sinus thrombosis following first exposure to the “COVID-19 vaccine AstraZeneca”. Methods: Patient files, laboratory findings, and diagnostic imaging results, and endovascular interventions of three concerning patients were evaluated in retrospect. Results: Three women with intracranial venous sinus thrombosis after their first vaccination with “COVID-19 vaccine AstraZeneca” were encountered. Patient #1 was 22 years old and developed headaches four days after the vaccination. On day 7, she experienced a generalized epileptic seizure. Patient #2 was 46 years old. She presented with severe headaches, hemianopia to the right, and mild aphasia 13 days after the vaccination. MRI showed a left occipital intracerebral hemorrhage. Patient #3 was 36 years old and presented 17 days after the vaccination with acute somnolence and right-hand hemiparesis. The three patients were diagnosed with extensive venous sinus thrombosis. They were managed by heparinization and endovascular recanalization of their venous sinuses. They shared similar findings: elevated levels of D-dimers, platelet factor 4 antiplatelet antibodies, corona spike protein antibodies, combined with thrombocytopenia. Under treatment with low-molecular-weight heparin, platelet counts normalized within several days. Conclusion: Early observations insinuate that the exposure to the “COVID-19 vaccine AstraZeneca” might trigger the expression of antiplatelet antibodies, resulting in a condition with thrombocytopenia and venous thrombotic events (e.g., intracranial venous sinus thrombosis). These patients’ treatment should address the thrombo-embolic manifestations, the coagulation disorder, and the underlying immunological phenomena.

Historical aspects of video endoscopic surgery of the lumbar spine

The literature review is devoted to the history of the development of endoscopic surgery of the lumbar spine: from open surgical interventions and puncture procedures – to percutaneous intracanal endoscopic operations, combining interventional and video endoscopic technologies and referred to in the English literature as “full-endoscopy”. The article also touches upon the historical aspects of fibroendoscopic and laparoscopic interventions on the lumbar spine. In conclusion, the principle of classification of endoscopic techniques is proposed.

Exosomal therapy-a new frontier in regenerative medicine

The recent advances in translational and nanomedicine have paved the way for developing the targeted drug delivery system at a greater pace among global researchers. On par with these technologies, exosomes act as a potential portal for cell-free drug delivery systems as these are bestowed with the native characteristics of the parent cell of origin. Exosomes, called extracellular vesicles (EcVs), are present in almost all cells, tissues, and body fluids. They help in intercellular signaling and maintains tissue homeostasis in the disease pathobiology. Researchers have characterized 9,769 proteins, 2,838 miRNAs, 3,408 mRNAs, and 1,116 lipids being present in exosomal cargo. The separation of exosomes from cells, tissues, and body fluids follow different patterned kinetics. Exosomes interact with the recipient cells through their surface receptor molecules and ligands and internalize within recipient cells through micropinocytosis and phagocytosis. Advancing technologies in regenerative medicine have facilitated the researchers to isolate exosomes from mesenchymal stem cells (MSCs) as these cells are blessed with supreme regenerative potentiality in targeting a disease. Exosomal cargo is a key player in establishing the diagnosis and executing therapeutic role whilst regulating a disease process. Various in vitro studies have exhibited the safety, efficacy, and therapeutic potentiality of exosomes in various cancers, neurodegenerative, cardiovascular, and orthopedic diseases. This article throws light on the composition, therapeutic role, and regulatory potentials of exosomes with the widening of the horizon in the field of regenerative medicine.

Proposed guidelines for treatment of recurrent failures for sustainability of results in the post-project improvement stage process

Purpose

The maintenance of process improvement programs within organizations is not an easy task. Some processes do not maintain the results achieved with the improvement project and again present low performance shortly after completion of the project. This paper aims to identify the socio-technical causes responsible for the loss of process performance after applying improvement projects, in order to support the mitigation of the problem.

Design/methodology/approach

A systematic review of the literature was carried out, which allowed the selection of 28 articles. The empirical stage used the benchmarking technique, along a large Brazilian mining company with an international standard of production and quality. This organization has been using improvement projects for more than ten years.

Findings

The research complements the literature regarding the prioritization of the 26 identified failures and the identification of seven new failure factors and two resources. Findings in this study can be an inspiration for other organizations, considering the similarity of methodological aspects of improvement projects since internationally standardized methodologies such as Six Sigma, Lean, Kaizen and 5S are used.

Originality/value

The research presented a proposal of guidelines that corroborate to the mitigation of loss of process performance after improvement project.

Application of Lean Six Sigma framework for improving manufacturing efficiency: a case study in Indian context

Purpose

This study aims to utilize DMAIC methodology along with value stream mapping and other Lean Six Sigma tools in a major automobile light manufacturing industry to reduce defect rates and increase production capacity in their manufacturing line. The study also proposes a modified framework based on lean principles and FlexSim to identify and reduce waste in the selected industry.

Design/methodology/approach

A Lean Six Sigma modified framework has been deployed with DMAIC to reduce the defect rate and increase the production rate. Various tools like value stream mapping, brainstorming, Pareto charts, 5S, kanban, etc. have been used at different phases of DMAIC targeting wastes and inventory in the production line. Also, a simulation model has been utilized for the automobile light manufacturing industry to improve the machine utilization time with varying batch sizes.

Findings

The results of the study indicated a 53% reduction in defect rates. Thus, there would be an expected improvement in sigma value from 3.78 to 3.89 and a reduction in defects per million opportunities (DPMO) from 11,244 to 8,493. Additionally, simulation model using FlexSim was developed, and the optimum ordering batch size of raw material was obtained. It was also analyzed that idle time for various stations could be reduced by up to 30%.

Practical implications

The utilized framework helps identify defects for managers to increase production efficiency. The workers, operators and supervisors on the production line also need to be trained regularly for identifying the areas of improvement.

Originality/value

The modified Lean Six Sigma framework used in this study includes FlexSim simulation to make the framework robust, which has not been used with LSS tools in the literature studied. Also, the LSS finds very less application in the manufacturing domain, considering which this study tends to add value in existing literature taking a case of an automobile light manufacturing industry.

Influence of slide burnishing process on the surface characteristics of precipitation hardenable steel

The surface integrity of the material is the predominant necessity of a component to perform efficiently in varying working conditions. To improve the surface integrity of the workpiece secondary finishing processes are being performed. This work attempts to propose a realistic cryogenic slide burnishing condition for improvement of the surface integrity. The slide burnishing was performed by a novel slide burnishing tool on 17–4 precipitation hardenable stainless steel. The experiment was designed based on a central composite design. Initially, the effect of control parameters on the output response was examined by experimental analysis based on the design of experiment. Analysis of variance was used to analyze the influence of the variables on the performance indices. The regression technique was used to develop an empirical model. Optimization of process parameters for finding minimum surface roughness and maximum surface hardness was achieved by a multi-objective genetic algorithm. The optimized solutions were validated by performing confirmation experiments.

Autologous bone marrow derived mesenchymal stem cell therapy for osteonecrosis of femoral head: A systematic overview of overlapping meta-analyses

STUDY DESIGN

Systematic Review.

OBJECTIVES

We performed this systematic overview on the overlapping meta-analyses that analyzed autologous bone marrow-derived mesenchymal stem cell(BM-MSC) therapy along with core decompression(CD) for the management of osteonecrosis of the femoral head(ONFH) and identify which study provides the current best evidence on the topic and generate recommendations for the same.

MATERIALS AND METHODS

We conducted independent and duplicate electronic database searches in PubMed, Web of Science, Embase, Cochrane Database of Systematic Reviews, and the Database of Abstracts of Reviews of Effects till September 2020 for meta-analyses that analyzed the efficacy of BM-MSC therapy along with CD for ONFH. Methodological quality assessment was made using Oxford Levels of Evidence, AMSTAR scoring, and AMSTAR 2 grades. We then utilized the Jadad decision algorithm to identify the study with the highest quality to represent the current best evidence to generate the recommendation.

RESULTS

6 meta-analyses fulfilling the eligibility criteria were included. The AMSTAR scores of the included studies varied from 4 to 9 (mean:7) and all the included studies had critically low reliability in their summary of results due to their methodological flaws according to AMSTAR 2 grades. The current best evidence showed that utilization of BM-MSC therapy along with CD for ONFH resulted in significant improvement in Harris hip scores at 12 and 24 months along with a significant reduction in the necrotic area of the femoral head and the rate of conversion to total hip arthroplasty(THA) without a significant rise in adverse events due to the procedure.

CONCLUSION

Based on this systematic overview, we give a Level II recommendation that BM-MSC therapy is more efficacious along with CD in the management of ONFH compared to CD alone. BM-MSC therapy provides better pain relief with significant functional improvement and delaying the collapse of the femoral head thereby preventing further treatment such as THA.

Making sense of the infodemic – A bibliometric analysis of publications on COVID-19 in trauma and orthopedics

The COVID-19 pandemic has prompted an explosion of publications to report, understand, further research, and manage this condition. While publications are analyzing the bibliometrics on this condition, there are none available specifically for the impact of COVID-19 on trauma and orthopedics. The aim of this study, therefore, was to perform a bibliometric analysis on COVID-19 and trauma and orthopedics to assess its impact on the specialty. A search for articles on COVID-19 concerning trauma and orthopedics, with the keywords: “COVID-19, New coronavirus, SARS-Cov-2, Orthopedic*, trauma, bone, and joint” were performed on the June 19, 2020, using SCOPUS and PUBMED and this resulted in 272 and 887 articles, respectively. Later, on the same day, we searched for orthopedic journals exclusively and extracted 258 articles from 58 journals. Furthermore, we analyzed the Altmetric data through the dimensions website to find the most popular articles on social media on this topic. After analyzing the data, we found that review articles were the most commonly published articles. The leading journal publishing this content were; The Journal of Bone and Joint Surgery (JBJS) American (35), followed by the Journal of Arthroplasty (22). There were 6936 authors involved in publishing 887 articles in 2020. Most articles were published by Vaishya (5) followed by Liang (5), and Iyengar (5). Analysis of Altmetric data showed a total number of citations of 5000 with a mean of 1.98. MedRxiv with 781 publications and 1616 citations was the preprint server with the most publications on dimensions. We studied details of the article with maximum AAS score of 25226 is with 840 citations. We have listed useful protocols from the search and top five cited articles from each search strategy. Publications on COVID-19 commenced from the 9th week of this year and have increased exponentially. Review articles (PubMed) and articles (Scopus) were the most published. The JBJS (Am) and J Arthroplasty have published the maximum number of articles on COVID-19. We found that for a fast evolving condition and for the short term, altmetrics may be better indicators than citations to follow directions of research. Publications with a low number of citations could have immense social media attention. This study should help in quantifying the value of research and publications related to orthopedics and trauma aspects of COVID-19 and therefore help the readers, researchers, and health-care providers to use this information effectively.

Bibliometric Study of Technology and Occupational Health in Healthcare Sector: A Worldwide Trend to the Future

Since the eighties, technological tools have modified how people interact in their environment. At the same time, occupational safety and health measures have been widely applied. The European Agency for Safety and Health at Work considers that information and communication technologies are the main methods to achieve the goals proposed to improve working life and the dissemination of good practices. The principal objective was to determine the trends of publications focused on these technologies and occupational safety in the healthcare sector during the last 30 years. A bibliometric study was carried out. The 1021 documents showed an increased trend per country, especially for the United States (p < 0.001) and year (p < 0.001). The citations per year showed significant differences between citations of articles published before 2007 (p < 0.001). The year was also linked to the increase or decrease of articles (72.2%) and reviews (14.9%) (p < 0.001). The analysis of journal co-citations also showed that the main journals (such as Infection Control and Hospital Epidemiology) were linked to other important journals and had a major part in the clusters formed. All these findings were discussed in the manuscript and conclusions were drawn.

Learning-Based Prediction of Pose-Dependent Dynamics

The constantly increasing demand for both, higher production output and more complex product geometries, which can only be achieved using five-axis milling processes, requires elaborated analysis approaches to optimize the regarded process. This is especially necessary when the used tool is susceptible to vibrations, which can deteriorate the quality of the machined workpiece surface. The prediction of tool vibrations based on the used NC path and process configuration can be achieved by, e.g., applying geometric physically-based process simulation systems prior to the machining process. However, recent research showed that the dynamic behavior of the system, consisting of the machine tool, the spindle, and the milling tool, can change significantly when using different inclination angles to realize certain machined workpiece shapes. Intermediate dynamic properties have to be interpolated based on measurements due to the impracticality of measuring the frequency response functions for each position and inclination angle that are used along the NC path. This paper presents a learning-based approach to predict the frequency response function for a given pose of the tool center point.

Aligning operational practices to competitive strategies to enhance the performance of Indian manufacturing firms

Purpose

The main purpose of this study is to understand how collective operational practices are adapted or stimulated by a firm's competitive strategy.

Design/methodology/approach

This study employed a data set drawn from 124 plant managers and directors of Indian manufacturing firms. Multiple regression was used to examine the impact of operational practices of lean, total quality management (TQM) and supply chain management (SCM) within competitive clusters of cost leadership, differentiation and focus strategy.

Findings

Results of the study show that the pattern of impact of operational practices on firm's performance varies according to type of the competitive strategy employed. All the three competitive strategy clusters have reported that TQM is the most important trigger for Indian manufacturing firms with relative effect of TQM practices on firm's performance being higher than that of lean and SCM practices.

Research limitations/implications

Cross-sectional data from Indian manufacturing firms were used, and it would be interesting to test the analytical framework of the study for more sectors and countries. Future studies can take a longitudinal research approach to strengthen the findings of the study.

Practical implications

The findings explain how operational practices are aligned with competitive strategies for practitioners so that they can assign limited resources to build diverse operational capabilities based on their strategic choices.

Originality/value

Although very few classical studies are reported in various contexts involving competitive strategy, operational practices and firm's performance, no existing study focuses on how these three domains are linked together in the context of Indian manufacturing sector.

Comparison of plate fixation vs. intramedullary fixation for the management of mid-shaft clavicle fractures: A systematic review and meta-analysis of randomised controlled trials

A number of meta-analyses have compared clinical outcomes following plate vs. intramedullary fixation for midshaft clavicle fractures (MSCF), but with conflicting results. There is a requirement for updated level-1 evidence to guide clinicians managing MSCF. The aim of the present systematic review and meta-analysis was to compare clinical outcomes following plate vs. intramedullary fixation of MSCF. The PubMed, Scopus, BioMed Central, Cochrane Central Register of Controlled Trials and Google Scholar databases were searched for records added until 1st July 2019. A total of 10 randomised controlled trials (RCTs) were included. Shoulder function was assessed using the Constant-Murley Shoulder Outcome questionnaire and the Disabilities of the Arm, Shoulder and Hand questionnaire (DASH). There was no statistically significant difference in Constant-Murley scores between plate and intramedullary fixation [Mean difference (MD)=0.75; 95% CI: -2.49 to 3.99; P=0.65; I²=85%]. Similarly, there was no statistically significant difference in DASH scores between the two groups (MD=1.55; 95% CI: -1.12 to 4.23; P=0.26; I²=89%). There was no statistically significant difference in complications requiring non-routine surgery between plate and intramedullary fixation [risk ratio (RR)=1.80, 95%CI: 0.80-4.05, P=0.15; I²=0%]. There was an increased risk of complications that did not require non-routine surgery with plate fixation as compared to intramedullary fixation (RR=2.38, 95%CI: 1.22-4.62, P=0.01; I²=70%). Plate fixation was also associated with an increased risk of infection and complications of cosmetic dissatisfaction. The present results indicated no difference in long-term functional outcomes between plate and intramedullary fixation of MSCF. Plate fixation was associated with an increased risk of complications not requiring non-routine surgery. Further high-quality RCTs shall strengthen the evidence on this subject.

Service quality evaluation of automobile garages using a structural approach

Purpose

The purpose of this paper is to evaluate the service quality automobile garages through development of a service quality index based on the factors influencing service quality.

Design/methodology/approach

A structural methodology of graph theory and matrix approach is applied for developing the service quality index.

Findings

The automobile maintenance can be considered as a service industry and in order to sustain in the competitive business environment, the service providers must ensure quality in their services. There are several factors that influence the service quality. Each factor is comprised of several sub-factors. Moreover, the factors are interrelated with each other. Modelling of these factors and their interrelations with due consideration of their structure is accomplished through the graph theory. The directed graph (digraph) of the service quality is defined; the nodes of this symbolize the quality influencing factors, while the edges represent their degrees of interrelationships. An equivalent matrix developed from the digraph establishes a service quality function which leads to evaluation of service quality index (SQI). A greater value of the service quality index displays that the organization and functioning of the garage is adequate.

Practical implications

The methodology can be applied for evaluating as well as comparing service quality of different garages. The observations would be helpful to the managers the garages to make strategies for improving their service quality.

Originality/value

The paper establishes the interrelations among various factors that influence the service quality at automobile garages and develop a numeric index for the evaluation of the same.

Comparison of radiological and clinical outcomes, complications, and implant removals in anatomically pre-contoured clavicle plates versus reconstruction plates - a propensity score matched retrospective cohort study of 106 patients

Background

Plate fixation is frequently used to treat displaced midshaft clavicular fractures, however the ideal plate choice remains subject to discussion; reconstruction locking compression plates (RLCPs) are cheaper and can be easily contoured, whereas anatomically pre-contoured locking compression plates (ALCPs) are thought to provide better stability and therefore lower rates of mechanical failure.

To compare the incidence of mechanical failures, functional and radiological outcomes in patients with midshaft clavicular fractures treated with ALCPs versus RLCPs.

Methods

A propensity score matched retrospective cohort study was conducted across two centers. One hundred and six consecutively recruited patients with displaced midshaft clavicular fractures, who were treated with plate fixation and had a minimum follow-up of 6 months, were matched on gender, age, fracture grading, energy of injury, and fracture location. The resulting groups included 53 ALCP-treated fractures and 53 matched controls treated with RLCPs.

Results

During a mean follow-up of 20.5 months, there were no implant deformities in the ALCP group whereas the RLCP group had 6 patients (11.3%, p = 0.012) with implant deformities (5 occurrences of plate bending with fracture union, and 1 plate breakage with nonunion). Despite the higher rate of plate deformities in the RLCP group, there were no statistically significant differences in number of patients recovering full shoulder range of motion (ALCP 90.6%, RLCP 88.7%, p = 0.751), incidence of rest pain (ALCP 13.2%, RLCP 9.4%, p = 0.542), or implant removals (ALCP 49.1%, RLCP 56.6%, p = 0.439).

Conclusion

ALCPs may be superior to RLCPs in terms of implant stability but appear to produce similar clinical results.

Exploring the effectiveness of maintenance and quality management strategies in Indian manufacturing enterprises

Purpose

The purpose of the paper is to examine the impact of human-related support practices, total productive maintenance (TPM) practices, and total quality management (TQM) practices on manufacturing performance parameters and their inter-relationship.

Design/methodology/approach

A research project was carried out in 94 Indian manufacturing companies, using the questionnaire method. The survey data was drawn from 169 respondents working in these companies. In this paper, the impact of TPM and TQM practices on manufacturing performance parameters and especially the role of support practices is investigated empirically using various structural equation models.

Findings

Two factors namely top management and leadership and human resource development categorized as support practices were found to positively influence the adoption of technical practices, i.e., TPM and TQM practices. Hence support practices were found to indirectly affect the manufacturing performance parameters via the technical factors. Also analyzing various structural equation models (SEM), shop floor implementation of TPM practices were found to be influenced (or guided) by the philosophy of TQM practices. In other words, through the proper adoption of TQM practices, the effectiveness of TPM practices gets increased.

Research limitations/implications

Because of the chosen research approach, the research results may lack generalizability. Therefore, researchers are encouraged to test the proposed propositions further using a case study approach.

Practical implications

The present study provides useful insights to practicing managers. The result of the study explaining the interrelationship between support practices (behavioral aspect) and technical practices can be used by practicing managers to develop a better understanding of the contribution of support and technical practices towards the realization of organizational objectives of growth and sustainability. In practice, TQM plays a great role in the adoption of TPM practices, which in turn helps to achieve quality in processes and therefore in products.

Originality/value

Previous research has often either concentrated on technical practices as one dimension without studying the effects of support practices on improving the adoption of technical practices. The results of the study take one step further by investigating the relationship between multiple aspects (support and technical aspects) of manufacturing practices and their impact on manufacturing performance.

Integrating DMAIC approach of Lean Six Sigma and theory of constraints toward quality improvement in healthcare

Healthcare is a unique service industry and it deals with complex tasks. To overcome complex tasks, healthcare organizations need to implement DMAIC (Define, Measure, Analyze, Improve, Control) approach of Lean Six Sigma (LSS) to improve quality performance. Application of DMAIC in a healthcare organization provides guidelines on how to handle a quality service system toward patient satisfaction. This approach also helps healthcare service providers to reduce waste, variation and work imbalance in the service processes. This chapter discusses five phases of DMAIC approach and its integration with the theory of constraints (TOC) for continuous improvements in healthcare performance. The integration of TOC and DMAIC approach would enhance healthcare performance by reducing medical costs, medical errors, administration errors and defects. Moreover, this integration can improve performance in healthcare service processes where it is not possible to reduce bottlenecks.

Fuzzy assessment analysis and key improvements to a production system

Purpose

The framework of Six Sigma Define-Measure-Analyze-Improve-Control was applied in this study, and various tools and techniques were used at different stages to implement lean measures to ensure quality. The purpose of this paper is to develop a decision-making framework that assesses key quality performance to ensure that practitioners improve quality and control by modeling and optimizing production processes.

Design/methodology/approach

A model of a quality performance index system was established. The weights of factors and sub-factors, which were estimated using an FAHP, were used as a reference for the decision maker under fuzzy uncertainly to make a decision, and thus, results present the bottlenecks in processes. Furthermore, any other factors that may affect the key process bottlenecks must be considered. The critical to quality characteristics were determined, and factor levels were set. The interaction between the factors was analyzed, their significance was studied using the Design of experiments and the parameters were predicted. Finally, quality improvement decisions were made through failure mode and effects analysis.

Findings

The implementation results of this research prove that the proposed model could successfully determine the key processes and focus on the improvement of critical quality factors under limited resources.

Originality/value

This study establishes a set of performance appraisal methods for production systems, which can be used for improving productivity and quality.

Application of Six Sigma DMAIC methodology to reduce the defects in a telecommunication cabinet door manufacturing process

Purpose

The purpose of this paper is to apply the Six Sigma DMAIC methodology in order to reduce the rejections experienced in the manufacturing of the doors belonging to a telecommunication cabinet.

Design/methodology/approach

The process involved joining of sheet metal and hinge using welding operations with the help of a fixture. The methodology used is the structured DMAIC method in order to identify the root cause for the rejections and solve it.

Findings

The paper provides insights about the identification of the root cause for the defects and the solution to overcome it, and also the benefits that were obtained as a result of the application of the solution.

Research limitations/implications

This methodology has been applied to the variation observed in the dimensions of a particular component to be welded with a main part. This approach can be used to find such dimensional variations.

Practical implications

This study has been successfully carried out in a medium-scale industry which has total quality management in practice.

Originality/value

Six Sigma DMAIC was necessary for the identification and reduction of the defects which arose in the sheet metal and welding operations, and had to be resolved in order to increase the bottom-line.

Justification of TPM pillars for enhancing the performance of manufacturing industry of Northern India

Purpose

The purpose of this paper is to assess TPM pillars for manufacturing performance improvement in the manufacturing organizations of Northern India and to identify critical and non-critical components based on failure history, to minimize machine downtime, maximize component/machine availability and to identify failure modes, their causes and effects of these failures on machines or components in the case company under study.

Design/methodology/approach

In this paper, TPM pillars in the paint manufacturing plant have been elaborated to ascertain the tangible and intangible benefits accrued as a result of successful TPM implementation. The approach has been directed toward justification of TPM implementation for its support to competitive manufacturing in the context of Indian manufacturing industries.

Findings

Findings suggest that maintenance planning is more effective than small improvements for achieving benefits from TPM pillars. Moreover, results indicated that critical components show average reliability and failure probability of about 50 percent.

Originality/value

The present study encompasses systematic identification of maintenance-related losses, setting up of targets regarding maintenance performance improvements and developing guidelines for achieving enhanced manufacturing system performance through strategic TPM implementation in the manufacturing plant, which can also be important to all concerned with maintenance in various manufacturing enterprises.

Analysis of Artificial Neural Network for Predicting Erosive Wear of Nylon-12 Polymer

In this study, artificial neural network (ANN) is applied to predict the erosion rate of nylon-12 polymer to ensure the accuracy of soft computing. The ANN model was developed with 4 neurons in the input layer, 10 neurons in the hidden layer, and 1 neuron in the output layer. A backpropagation algorithm was utilized in a multilayered perception. The inputs include impact velocity (m/s), impingement angle (°), erodent size (μm), and stand-off distance (mm). Experimental data were used to predict the erosion rate in relation to the input parameters. The size of the erosive element of randomly shaped sand particles (silicon dioxide) is set between 300 and 600 μm, the impact velocity between 30 and 50 m/s, the impingement angle between 30° and 90°, and the stand-off distance between 15 and 25 mm. The consistency between the experimental and ANN model values, with an accuracy of 94.428 % and root mean square error of 9.729, signifies that the proposed ANN model is suitable for predicting the erosion rate of nylon-12 polymer. The prediction made using the ANN model was in good agreement with the experimental results. The ANN model can be used to estimate the maximum and total erosion rate of nylon-12 with high reliability. Therefore, this model can be applied for practical purposes.

Parametric Optimization of Trochoidal Step on Surface Roughness and Dish Angle in End Milling of AISID3 Steel Using Precise Measurements

Tool steel play a vital role in modern manufacturing industries due to its excellent properties. AISI D3 is a cold work tool steel which possess high strength, more hardenability and good wear resistance properties. It has a wide variety of applications in automobile and tool and die making industries such as blanking and forming tools, high stressed cutting, deep drawing and press tools. The novel ways of machining these steels and finding out the optimum process parameters to yield good output is of practical importance in the field of research. This research work explores an attempt to identify the optimized process parameter combinations in end milling of AISI D3 steel to yield low surface roughness and maximum dish angle using trochoidal milling tool path, which is considered as a novelty in this study. 20 experimental trials based on face centered central composite design (CCD) of response surface methodology (RSM) were executed by varying the input process factors such as cutting speed, feed rate and trochoidal step. Analysis of variance (ANOVA) was adopted to study the significance of selected process parameters and its relative interactions on the performance measures. Desirability-based multiple objective optimization was performed and the mathematical models were developed for prediction purposes. The developed mathematical model was statistically significant with optimum conditions of cutting speed of 41m/min, feed rate of 120 mm/min and trochoidal step of 0.9 mm. It was also found that the deviation between the experimental and predicted values is 6.10% for surface roughness and 1.33% for dish angle, respectively.

Six Sigma 4.0

Der vorliegende Beitrag vergleicht Six-Sigma- und Data-Mining-Methoden im Hinblick auf das Null-Fehler-Management in Produktionsprozessen. Darauf aufbauend wird ein Six-Sigma-4.0-Prozessmodell abgeleitet, das die Stärken beider Ansätze vereint und somit einen Handlungsleitfaden für Verbesserungsprojekte im Rahmen der Indus-trie 4.0 bereitstellt. Das vorgestellte Six-Sigma-4.0-Modell wird im Zuge eines Verbesserungsprojekts im Bereich der Elektronikproduktion validiert.

Modeling of surface roughness for manufactured thin-walled structure

Deformation of thin-walled structure during machining will influence the surface quality of the final part. Present article investigates this problem and develops a method to predict the surface roughness of the machined surface. To achieve this, the prerequisite is to obtain the dynamic deformation along the milling path. To calculate it accurately, the workpiece is simplified as thin-walled shell and the milling force is simplified as moving input. An expression of the dynamic deformation of the whole structure, which under the excitation of moving milling force, is derived by solving the vibration equation using modal superposition method. Then, the deformation along the milling path is computed by substituting the path coordinates into the expression. The deformation along the milling path is filtered to remove its low-frequency and mid-frequency signals before it is used to evaluate the surface roughness of the machined surface. At last, several machining cases are implemented to demonstrate the proposed method. The experimental results match well with the predicted results. From the predicted and experimental results, it is founded that the deformation during processing is the main reason leading to the poor surface quality of the flexible machined workpiece.

Novel patch shape design to repair π/4 quasi-isotropic E-glass/epoxy laminate under uniaxial tensile loading condition

The entitled technical subject in its comprehensive and broadly viewed study is presented by stating that the prevailing glass fiber–reinforced plastic composites play a vital role in replacing the metallic structures in automotive, aerospace, and marine applications and their more usage necessitates the better understanding of such structure’s damage and effective repair practices of the same. In the course of repairing the composite structures, optimum usage of patch material helps to maintain the original strength, eliminate “over design,” and reduce contribution to the substantial performance change of original structure. Optimum usage of repair material brings down the significant percentage of mass and repair cost. In order to apply the concept of optimum patch shapes over actual structures, it is important to design such effective shapes which are equivalent to the conventionally proven repair designs in strength perspective. This technical paper describes one of such ways to design the optimum patch shape using finite element analysis (FEA) tool and in comparison with one of the conventional repair practices, like circular patching, used circular, rectangular, square, elliptical and trapezoidal patch shapes, each of which has its own merits and demerits when compared to the other. But, none of them was arrived at in the perspective to use the minimum material to repair the damage. The object of this work is carried out in order to arrive at the optimum patch shape (minimum material in its in-plane direction) in repairing the damaged structure and it has been demonstrated using π/4 quasi-isotropic E-glass/epoxy specimen with hole using FEA. Moreover, the effectiveness of optimum patch shape design in “strength” and “load transfer efficiency” perspectives is experimentally proven and highlighted by the scope of repair material saving (36%) in repair practice by the usage of this optimized approach, as well.

Research on surface roughness prediction method based on composite penalty regression model

With the development of manufacturing technology, traditional empirical formulas are hard to deal with the relationships between complex manufacturing techniques and surface roughness. Current data fitting-based modeling methods often do not consider the influence of various factors on surface roughness and lack data cleaning capability. This paper proposes a method to reduce the dimension of data features, which includes the Lasso model to determine the correlation degree of processing parameters and roughness, and solves the possible sparse coefficient relationship between processing parameters and roughness. The ridge regression is also introduced to predict the workpiece surface roughness. The results show that compared with the existing prediction model, this prediction method has high accuracy when given a small amount of training data.

Critical review and analysis of measuring the success of Six Sigma implementation in manufacturing sector

Purpose

The purpose of this paper is to capture the status of implementation of Six Sigma in various manufacturing industries and also examine the success of the Six Sigma by using different performance indicators.

Design/methodology/approach

The methodology of critical review involves the selection and classification of 112 research articles on the implementation of Six Sigma in different manufacturing industries. The selected articles are categorized by the following: articles distribution based on the year of publication, publication database, various journals, contribution of authors, continent, scale of industry, implemented approaches, focused industry, tools and techniques used in phases of Six Sigma methodology, and performance indicators used in Six Sigma implementation. Then after, future scopes of research opportunities are derived based on significant findings.

Findings

The literature revealed that: Very few work was undertaken on the implementation of Six Sigma in various manufacturing industries like ceramic, paper, gems and jewelry, cement, furniture, stone, fertilizer, forging, paper and surface treatment industries. Most of the researchers have considered very few performance indicators to identify the improvement after Six Sigma implementation. But, there is no clue regarding overall improvement in different perspectives after the implementation of Six Sigma. The financial indicators, personnel indicators, process indicators and customer indicators are useful to measure the overall improvement after the implementation of Six Sigma in the manufacturing sector.

Research limitations/implications

The study was carried out on the implementation of Six Sigma methodology in various manufacturing industries, and various performance indicators were identified while implementing the Six Sigma methodology. Case studies pertaining to service industries were not covered here.

Originality/value

Very little research has been carried out to measure the overall success of implementing Six Sigma methodology in manufacturing industries. This paper will provide value to students, researchers and practitioners of Six Sigma by providing insight into the implementation of Six Sigma in manufacturing industries.

ANN Surface Roughness Optimization of AZ61 Magnesium Alloy Finish Turning: Minimum Machining Times at Prime Machining Costs

Magnesium alloys are widely used in aerospace vehicles and modern cars, due to their rapid machinability at high cutting speeds. A novel Edgeworth–Pareto optimization of an artificial neural network (ANN) is presented in this paper for surface roughness (Ra) prediction of one component in computer numerical control (CNC) turning over minimal machining time (T_m) and at prime machining costs (C). An ANN is built in the Matlab programming environment, based on a 4-12-3 multi-layer perceptron (MLP), to predict Ra, T_m, and C, in relation to cutting speed, v_c, depth of cut, a_p, and feed per revolution, f_r. For the first time, a profile of an AZ61 alloy workpiece after finish turning is constructed using an ANN for the range of experimental values v_c, a_p, and f_r. The global minimum length of a three-dimensional estimation vector was defined with the following coordinates: Ra = 0.087 μm, T_m = 0.358 min/cm³, C = $8.2973. Likewise, the corresponding finish-turning parameters were also estimated: cutting speed v_c = 250 m/min, cutting depth a_p = 1.0 mm, and feed per revolution f_r = 0.08 mm/rev. The ANN model achieved a reliable prediction accuracy of ±1.35% for surface roughness.

Deploying Six Sigma practices to General Electric subsidiaries in a developing economy

Purpose

The purpose of this paper is to investigate Six Sigma implementation in the subsidiaries of General Electric (GE) located in Brazil and to explore the role of the quality culture of headquarters in overcoming common obstacles to Six Sigma implementation reported by other studies.

Design/methodology/approach

An exploratory survey was the basis for gathering data for this study. A structured questionnaire was developed covering issues related to Six Sigma implementation, such as experienced benefits, main outcomes, and metrics adopted by companies. Data from eight GE subsidiaries were qualitatively analyzed. The findings were discussed in the light of other studies conducted in Brazil as well as in other developing countries in the context of the role of existing quality culture in overcoming barriers to Six Sigma implementation.

Findings

The findings revealed that Six Sigma at GE subsidiaries achieved better results in comparison with the results obtained by other Brazilian companies reported in the literature. GE quality culture aspects such as top management commitment, high investment in training, recognition schemes, and development of a well-planned infrastructure were identified as valuable to overcome common barriers to Six Sigma implementation. Moreover, the findings showed a strong alignment with the goals and practices of GE headquarters, which is an evidence of the quality culture that exists in GE and that allows all GE businesses achieve benefits with Six Sigma.

Originality/value

Since limited empirical research has been conducted concerning Six Sigma implementation in developing countries, this paper aspires to contribute to Six Sigma body of knowledge by illustrating the practices of a world benchmark corporation.

Prediction of Cutting Conditions in Turning AZ61 and Parameters Optimization Using Regression Analysis and Artificial Neural Network

All manufacturing engineers are faced with a lot of difficulties and high expenses associated with grinding processes of AZ61. For that reason, manufacturing engineers waste a lot of time and effort trying to reach the required surface roughness values according to the design drawing during the turning process. In this paper, an artificial neural network (ANN) modeling is used to estimate and optimize the surface roughness (Ra) value in cutting conditions of AZ61 magnesium alloy. A number of ANN models were developed and evaluated to obtain the most successful one. In addition to ANN models, traditional regression analysis was also used to build a mathematical model representing the equation required to obtain the surface roughness. Predictions from the model were examined against experimental data and then compared to the ANN model predictions using different performance criteria such as the mean absolute error, mean square error, and coefficient of determination.