Statistical process control is an excellent quality assurance tool to improve the quality of manufacture and ultimately scores on end-customer satisfaction. SPC uses process monitoring charts to record the key quality characteristics (KQCs) of the component in manufacture. This paper elaborates on one such KQC of the manufacturing of a connecting rod of an internal combustion engine. Here the journey to attain the process potential capability index (C p ) and the process performance capability index (C pk ) values greater than 1.33 is elaborated by identifying the root cause through quality control tools like the cause-and-effect diagram and examining each cause one after another. In this paper, the define-measure-analyze-improve-control (DMAIC) approach is employed. The definition phase starts with process mapping and identifying the KQC. The next phase is the measurement phase comprising the cause-and-effect diagram and data collection of KQC measurements. Then follows the analysis phase where the process potential and performance capability indices are calculated, followed by the analysis of variance (ANOVA) of the mean values. Finally, the process monitoring charts are used to control the process and prevent any deviations. By using this DMAIC approach, standard deviation is reduced from 0.48 to 0.048, the C p values from 0.12 to 1.72, and the C pk values from 0.12 to 1.37, respectively.

The define-measure-analyze-improve-control (DMAIC) approach is a five-strata approach, namely DMAIC. This approach is the scientific approach for reducing the deviations and improving the capability levels of the manufacturing processes. The present work elaborates on DMAIC approach applied in reducing the process variations of the stub-end-hole boring operation of the manufacture of crankshaft. This statistical process control study starts with selection of the critical-to-quality (CTQ) characteristic in the define stratum. The next stratum constitutes the collection of dimensional measurement data of the CTQ characteristic identified. This is followed by the analysis and improvement strata where the various quality control tools like Ishikawa diagram, physical mechanism analysis, failure modes effects analysis and analysis of variance are applied. Finally, the process monitoring charts are deployed at the workplace for regular monitoring and control of the concerned CTQ characteristic. By adopting DMAIC approach, standard deviation is reduced from 0.003 to 0.002. The process potential capability index (C P ) values improved from 1.29 to 2.02 and the process performance capability index (C PK ) values improved from 0.32 to 1.45, respectively.

Drawing is a visual mode of communication. Teaching drawing requires one-to-one personal interaction among the tutor and the learner. The technical drawing is no exception, and it requires a considerable amount of imagination skills. On-line mode of pedagogy shall be occupying a substantial portion of the mode of delivery in teaching and learning during, as well as, after the coronavirus disease 2019 (COVID-19) pandemic era. This work focuses on the training and knowledge sharing of machine drawing skills through online mode, which is the requirement of the present era. A knowledge management perspective for machine drawing pedagogy is involved in this work. Challenges in the online pedagogy of machine drawing are deliberated through Ishikawa diagram and service Failure Modes and Effects Analysis. A maker education perspective of online machine drawing pedagogy is delineated. An approach toward knowledge workforce, knowledge transfer, and tacit knowledge is adopted for online teaching of machine drawing. Finally, conclusions are drawn in context of online pedagogy for a spatial visualization-based course like machine drawing.

Engineering drawing is a basic engineering course, which is popularly remembered as the language of engineers and finds the applications in all the domains of engineering as well as architecture. And now due to the intervention of computing facility, it gained further momentum in the field of engineering and technology. This paper traces the development of higher order thinking (HOT) skills in the field of engineering drawing. This paper makes an attempt in proposing distinct platforms for inculcating higher order thinking skills among the engineering students, which further enables them to achieve their highest potential and prepare them to propose solutions for the real world problems. Spatial visualization coupled with an intensive practise in free-hand sketches and manual drafting which is slowly dwindling in today's era of computerization, is proposed for improving HOT skills in the domain of engineering drawing. Students' understanding of the engineering drawing course has registered a substantial improvement and is recorded in the assessment performed.

This paper first enlists the generic problems of alloy wheel machining and subsequently details on the process improvement of the identified critical-to-quality machining characteristic of A356 aluminum alloy wheel machining process. The causal factors are traced using the Ishikawa diagram and prioritization of corrective actions is done through process failure modes and effects analysis. Process monitoring charts are employed for improving the process capability index of the process, at the industrial benchmark of four sigma level, which is equal to the value of 1.33. The procedure adopted for improving the process capability levels is the define-measure-analyze-improvecontrol (DMAIC) approach. By following the DMAIC approach, the C p , C pk and C pm showed signs of improvement from an initial value of 0.66, -0.24 and 0.27, to a final value of 4.19, 3.24 and 1.41, respectively.

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High-density polyethylene (HDPE) pipes find versatile applicability for transportation of water, sewage and slurry from one place to another. Hence, these pipes undergo tremendous pressure by the fluid carried. The present work entails the optimization of the withstanding pressure of the HDPE pipes using Taguchi technique. The traditional heuristic methodology stresses on a trial and error approach and relies heavily upon the accumulated experience of the process engineers for determining the optimal process control parameters. This results in setting up of less-than-optimal values. Hence, there arouse a necessity to determine optimal process control parameters for the pipe extrusion process, which can ensure robust pipe quality and process reliability. In the proposed optimization strategy, the design of experiments (DoE) are conducted wherein different control parameter combinations are analyzed by considering multiple setting levels of each control parameter. The concept of signal-to-noise ratio (S/N ratio) is applied and ultimately optimum values of process control parameters are obtained as: pushing zone temperature of 166°C, Dimmer speed at 08 rpm, and Die head temperature to be 192°C. Confirmation experimental run is also conducted to verify the analysis and research result and values proved to be in synchronization with the main experimental findings and the withstanding pressure showed a significant improvement from 0.60 to 1.004 Mpa.

In the present pedagogical work, the importance of teaching mechanical engineering concepts using three-dimensional spatial visualization was emphasized and explained using specific examples. Elementary concepts of the mechanical engineering such as vortex flow, geometric and dimensional tolerances, orthographic projections, machine components, and hydraulic machinery were depicted in three dimensions, using a computer-aided geometric modeling software. The conventional schematic methods used to describe the mechanical engineering concepts were mapped into spatial three-dimensional geometric models. These three-dimensional geometric models bring clarity in understanding the complex engineering concepts in an accurate and precise way because of the ease in visualization. An improvement in students’ level of understanding is recorded through percentage marks obtained in the students’ performance in the classroom environment.