A framework for six-sigma implementation in rubber manufacturing industry – an innovation between DMAIC cycle and quality improvement tools

Quality improvement tools are commonly utilised by the industries to attain quality products and benefits like reduction in scrap cost and wastes. In order to achieve the proper implementation of quality tools, a theoretically developed framework inclusive of six-sigma DMAIC (Define, Measure, Analyse, Improve & Control) cycle is required. Also, the quality tools associated at each stage has thoroughly implemented on a case study which carries a real-time issue related to the quality products production. The issue has thoroughly resolved through the right application of quality tools like Failure Modes and effects analysis (FMEA) on the compression moulding technique utilised for the production of Rubber Valve Sleeve Liner (RVSL) under the umbrella of DMAIC cycle. The benefits achieved are 23.1% reduction in scrap rate, 63.8% reduction in Delivery on time (DOT) with savings gained almost RM26,880/month. The relationship between DMAIC cycle and quality tools for quality improvements under the platform of lean six sigma which is highly beneficial for academicians, practitioners and engineering managers working in this field with a limitation of implementation only in the rubber manufacturing industry. In future, the developed framework should be implemented in some other manufacturing industries

Sustainable waste solutions: Optimizing location-allocation of 3R waste management sites in Gondokusuman, Yogyakarta, Indonesia through multi-maximal covering location approach

Developing a Multi-Maximal Covering Location Model (MMCLM) for waste management in Gondokusuman Sub-district, Yogyakarta, Indonesia, is urgently needed. The closure of the Piyungan landfill has resulted in the need for additional Reduce, Reuse, and Recycle Waste Management Sites (3R-WMSs) to reduce waste that the landfill cannot accommodate. The primary objective of this model is to optimize the location and allocation of demand volume nodes, representing the resident population, to a specific set of 3R-WMS. These demand nodes are located at different distances from 3R-WMSs, including high and low coverage areas. The research in the Gondokusuman Sub-district employed MMCLM with facility capacity constraints and was developed using mixed integer linear programming methodology. The study identified five optimal locations for a 3R-WMS establishment that comprehensively cover all demand nodes (15301) and population clusters (45903) in the sub-district, including both high (5085) and low coverage areas (10216). This research represents a significant step forward in developing a sustainable environment by ensuring easy access to reducing, reusing, and recycling-based waste management facilities for residents

A trail to milieu research methodology for application of implementation frameworks in manufacturing sector

The profusely used tools of operational management research in lean manufacturing context include roadmap, conceptual model, implementation frameworks, descriptive planning and assessment checklist. Out of these, an implementation framework development in lean manufacturing sector is common, but faces quandary regarding its development, consolidation and validation – thereby confirming the requirement of availability of succinct platform that aids in research methodology development. The aim of this research is to attain a clear research context, achieved accordingly by detailed literature review study that would subsequently aid in developing a generic research methodology design framework. Concomitant to it, the four layers, the layers of research onion were discussed; followed by selection of appropriate methods for development of research methodology in order to arrive at implementation frameworks. It was observed that for the methodology development, the philosophy of pragmatism is highly suitable, followed by abductive logic, in case of technique, mixed mode research is best, whereas in strategy selection, case study strategy is the most suitable due to its multi-functional ability of in-depth operational study. In addition to that, the mixed-mode approach carries the ability of comparative qualitative and quantitative research through longitudinal and cross-sectional case study respectively. Furthermore, the data collection processes were discussed in relevance to the research objective, which culminated in the formation of a detailed research methodology which has been divided into three major stages of research context and approach, framework development and validation, resulting in attaining implementation framework through literature review, longitudinal case study and cross-sectional case study respectively. The major strength and contribution of this research study is the development of one concise research methodology that is considered as the paradigm shift and a clear innovation towards this field

Project managers' personality and project success : moderating role of external environmental factors

Successful project completion is a challenging phenomenon for project managers. Various factors play an indispensable role in the success of a project. The objective of this study is to examine the role of project managers’ personalities in project success with the moderating role of external environmental factors i.e., political, economic, social. The study includes 145 project managers from 36 large‐scale construction projects, from both the public and private sectors. The big five personality model was used to evaluate the personality traits of project managers and triple constraint criteria (cost, time, and quality) was used to gauge project success. Data has been collected through a well‐structured questionnaire. The analysis of data indicated that personality traits like extraversion and openness are positive predictors of project success, whereas conscientiousness, agreeableness, and neuroticism did not have any direct relationship with project success. Importantly, the findings of this study concluded that external environmental factors—like political, economic, and social— moderately influence the link of specific project managers’ personality traits to project success. The role of external environmental factors as moderators has been discussed. The findings indicate the essential personality traits, as well as the role of external factors for achieving project success. The research contributions have relevance to both theory and practice and provide a deeper insight that is useful for individuals, organizations, researchers, practitioners, and decision‐makers

Knowledge creation dynamics of technological forecasting and social change special issues

Technological Forecasting and Social Change (TFSC) is a leading peer-reviewed journal that addresses issues at the intersection of technology and society. A major strategy of the journal is to actively solicit and publish Special Issues (SIs). These SIs were first launched in 1979 to highlight and solicit manuscripts from the “hot” emerging issues of the discipline. This paper aims to analyze SIs and to highlight it's impact on TFSC as compared to Regular Issues (RIs). Using bibliometric analysis, this study first establishes that SIs have a higher impact on the field than RIs when evaluated based on average citations per manuscript, percentage of ‘hot’ papers, and the rate of citations per annum. The study then identifies leading actors (authors, affiliated institutions, and countries) and journals (knowledge inflow/outflow) that have contributed to the success of TFSC-SIs. Finally, using bibliographic coupling, seven thematic clusters of TFSC's SIs were identified. These clusters were compared with the knowledge clusters developed by Singh et al. (2020) for the entirety of TFSC journals, and four clusters unique to SIs were identified i.e. (Climate Change & Energy, Entrepreneurship and Innovation, Sustainability and, Social Media & Internet of Things). It is observed that these unique SI clusters have received disproportionate attention during the last decade and are likely to influence the future trajectory of the journal

Production Enhancement through Integration of Lean, Life Cycle Assessment & Industry 4.0

Advancement in the manufacturing sector has attained a dominate interest from the researchers as well as the industrialists, for attaining the more products efficiencies. The concept of Lean Manufacturing set the cornerstone for excellence in manufacturing sector by improving the production times and reducing the non-value-added processes. In 2011, the concept of Industry 4.0 pivoted the concept of automation in factories to complement the production improvement processes. The under developing countries such as Pakistan, the manufacturing sector is run with the conventional manufacturing practices, which yields the products of lower quality and much time is being wasted resulting in overall poor efficiency. Moreover, those industries which want to improve their processes are not very much certain, about the methodologies they shall implement. In this research study, the authors have used the mathematical modelling approach of Analytical Hierarchy Processes (AHP) to recognise the pertinent Industry 4.0 technologies and lean perceptions – this technique empowers opportunity of organizing and analysing the intricate decisions for a strong understanding. By using Value Stream Mapping and Automation in a simulation-based case study, improvements of 44.70% in lead time, 17% in value added time and 45.25% in non-value-added time were witnessed. This research explores the avenue of Multi-Criteria Decision-Making (MCDM), based decision making in Industry 4.0 related environments. It will provide clarity to academicians regarding the integration of lean and Industry 4.0 through optimized and logical selection of relevant approaches, in addition to aiding practitioners in intelligent decision making

Essential elements for Radio Frequency Identification (RFID) adoption for industry 4.0 Smart Manufacturing in Context of Technology-Organization-Environment (TOE) Framework – a review

Automatic identification and data collection provides an ideal basis for Industry 4.0 Smart Manufacturing. The manufacturing sectors, involving a wide spectrum of physical and digital world, are functioning in extremely challenging environment. To optimize production efficiency, the incorporation of automated data collection technologies such as Bar Code and Radio Frequency Identification (RFID) is essential. Both these technologies have a great overlap in terms of industrial applications and no study reviews the existing literature in this regard. Therefore to cope up this matter, a systematic literature review has been conducted in which the technologies have been studied and compared, followed by the detailed discussion under various contexts of Technology-Organization-Environment (TOE) Framework. It has been observed that both these technologies have been employed in various manufacturing domains such as lean manufacturing, inventory management and production planning. However, it has been observed that RFID technology carried technological superiority over Bar Code technology. The systems utilizing the former are highly reliable, exquisitely capable and perform excellent in case of automation. However, issues such as high capital costs and increased level of technical complexity are few dilemmas in case of adopting RFID based systems. In addition to that, the implementation of RFID systems is complemented by certain essential features of TOE framework, which can help to elevate competitiveness and efficiency of an organization regarding tracking and identification of assets and inventory

Intra-abdominal desmoplastic small round cell tumor

Intra-abdominal desmoplastic small round cell tumor (IDSRCT) is a unique, highly aggressive neoplasm that chiefly affects male adolescents and young adults and most frequently presents as a large abdominal mass with widespread peritoneal involvement at the time of diagnosis. We present two cases of IDSRCT in a young male and a female. Both typically presented with diffuse peritoneal involvement

Assessment of risk factors associated with diabetes: Assessment of risk factors associated with diabetes

Abstract: Objective: Purpose of the study was to assess to risk factors of diabetes type II and complications in diabetic patient of tertiary care hospital. Methods/Design: Cross sectional study conducted to evaluate the risk factors associated with diabetes Mellitus. Setting: Tertiary hospitals of Islamabad and Azad Kashmir was selected for the current study. Participants: 50 patients assessed without any gender discrimination age between 35 to 85 years for risk factors and complications. Intervention: Data was collected from patients that were bed ridden admitted in hospitals. A total of 50 patients were included in this study with age limit more than 35 years and without any discrimination of gender. Primary Outcome Measures:  In tertiary care hospitalized patient’s obesity, inactivity and family history were the major risk factor for diabetes mellitus type 2 and we calculated the obesity, inactivity and family history percentage in diabetic patients 63%, 49% and 67% respectively. Results: Percentage of risk factors calculated the obesity, inactivity and family history in diabetic patients 63%, 49% and 67% respectively. Macro vascular complications in patients with diabetes mellitus type 2 were stroke 3%, angina 8%, hypertension and cognitive impairment have highest percentages i.e., 78%. 46% patients were suffering from ulceration; gangrene and amputation have percentages 19% and 3% respectively. Patients with microvascular complications of diabetic nephropathy were assessed for their albuminuria 25%, edema 32% and incontinence 28%. Conclusion: These complications can be avoided if patients of DM type 2 adopt a healthy lifestyle, do exercise and monitor their blood glucose levels regularly. Patients should also control their blood pressure to avoid damage to their microvasculature