Quality engineering of a traction alternator by robust design

Bhat²,

Antony

et al. 2021

TQM

PurposeThis article aims to provide Design for Six Sigma (DFSS) practitioners, researchers and academicians with Ten Commandments to successfully deploy projects.Design/methodology/approachThe commandments are the brainchild of four authors' experience and expertise for more than 15 years of DFSS deployment in the spectrum of fields as a consultant, researcher, academic and Master Black Belt in Six Sigma and general quality management and engineering disciplines. Thus ascertained commandments were validated and classified through the “Delphi Study” to ensure its applicability.FindingsThe Ten Commandments from authors' perspective include: alignment of DFSS with organisational strategy; top management support and involvement; listening to the voice of the customers (VOC); effective training programme for right project teams; project selection and prioritisation; linking DFSS with ISO international standards; linking DFSS with organisational learning and innovation; linking DFSS with the 4th Industrial Revolution; effective use of DFSS methodology and the integrated tools within the methodology and reward and recognition schemes.Research limitations/implicationsThe commandments presented in this article are the authors' personal experience in different industrial scenarios and settings and demographical locations. The authors are planning to conduct a longitudinal survey to understand further insights of these commandments with the input of several DFSS Black Belts and Master Black Belts, academicians and leading researchers from various countries.Originality/valueAll the organisation's stakeholders can use this article as general guidelines to ensure effective deployment of the DFSS approach.

Section: Use Of Dfss Methodology and The Integrated Tools Within The Methodologymentioning

confidence: 99%

Ten commandments for successful implementation of Design for Six Sigma

Bhat²,

Antony

et al. 2021

TQM

“…The design layout thus developed for the experiment by allocating the factors and level to the L 8 (2 7 ) orthogonal array (OA) is shown in Table 7. The experimental sequence as per the design was randomized, and the TAT was recorded (Acharya et al, 2010). The collected data was subjected to Taguchi's DOE analysis in the Minitab Software.…”

Section: Analyze Phasementioning

confidence: 99%

Lean Six Sigma competitiveness for micro, small and medium enterprises (MSME): an action research in the Indian context

Bhat¹,

Rego

et al. 2020

TQM

PurposeThe aim of the article is to ascertain the challenges, lessons learned and managerial implications in the deployment of Lean Six Sigma (LSS) competitiveness to micro, small and medium Enterprises (MSME) in India and to establish doctrines to strengthen the initiatives of the government.Design/methodology/approachThe research adopts the Action Research methodology to develop a case study, which is carried out in the printing industry in a Tier III city using the LSS DMAIC (Define-Measure-Analyze-Improve-Control) approach. It utilizes LSS tools to deploy the strategy and to unearth the challenges and success factors in improving the printing process of a specific batch of a product.FindingsThe root cause for the critical to quality (CTQ) characteristic, turn-around-time (TAT) is determined and the solutions are deployed through the scientifically proven data-based approach. As a result of this study, the TAT reduced from an average of 1541.2–1303.36 min, which in turn, improved the sigma level from 0.55 to 2.96, a noteworthy triumph for this MSME. The company realizes an annual savings of USD 12,000 per year due to the success of this project. Top Management Leadership, Data-Based Validation, Technical Know-how and Industrial Engineering Knowledge Base are identified as critical success factors (CSFs), while profitability and on-time delivery are the key performance indicators (KPIs) for the MSME. Eventually, the lessons learned and implications indicate that LSS competitiveness can be treated as quality management standards (QMS) and quality tools and techniques (QTT) to ensure competitive advantage, sustainable green practices and growth.Research limitations/implicationsEven though the findings and recommendations of this research are based on a single case study, it is worth noting that the case study is executed in a Tier III city along with novice users of LSS tools and techniques. This indicates the applicability of LSS in MSME and thus, the modality adopted can be further refined to suit the socio-cultural aspects of India.Originality/valueThis article illustrates the deployment of LSS from the perspective of novice users, to assist MSME and policymakers to reinforce competitiveness through LSS. Moreover, the government can initiate a scheme in line with LSS competitiveness to complement the existing schemes based on the findings of the case study.

“…Structured continuous improvement approach is paramount in I4.0 to ensure value proposition, robust technology and sustainable system. One of the proven tools of Industry 3.0 is the Lean Six Sigma (LSS) to ensure value proposition and robust technology/engineering by improving the processes in the industry (Acharya et al , 2010; Gijo et al , 2014). LSS is the fusion of Lean Manufacturing, also known as Lean Thinking at the strategic level, an approach which concentrates on banishing the wastes to establish value proposition in the system, and the Six Sigma methodology to reduce variation to establish robust technology (Antony et al , 2016a; Bhat et al , 2014).…”

Section: Introductionmentioning

confidence: 99%

Simulation-based lean six sigma for Industry 4.0: an action research in the process industry

Bhat

Bhat²,

2020

IJQRM

PurposeThe primary aim of this article is to ascertain the modalities of leveraging Lean Six Sigma (LSS) for Industry 4.0 (I4.0) with special reference to the process industries. Moreover, it intends to determine the applicability of simulation-based LSS in the automation of the mineral water industry, with special emphasis on the robust design of the control system to improve productivity and performance.Design/methodology/approachThis study adopts the action research methodology, which is exploratory in nature along with the DMAIC (define-measure-analyze-improve-control) approach to systematically unearth the root causes and to develop robust solutions. The MATLAB simulation software and Minitab statistical software are effectively utilized to draw the inferences.FindingsThe root causes of critical to quality characteristic (CTQ) and variation in purity level of water are addressed through the simulation-based LSS approach. All the process parameters and noise parameters of the reverse osmosis (RO) process are optimized to reduce the errors and to improve the purity of the water. The project shows substantial improvement in the sigma rating from 1.14 to 3.88 due to data-based analysis and actions in the process. Eventually, this assists the management to realize an annual saving of 20% of its production and overhead costs. This study indicates that LSS can be applicable even in the advent of I4.0 by reinforcing the existing approach and embracing data analysis through simulation.Research limitations/implicationsThe limitation of this research is that the inference is drawn based on a single case study confined to process industry automation. Having said that, the methodology deployed, scientific information related to optimization, and technical base established can be generalized.Originality/valueThis article is the first of its kind in establishing the integration of simulation, LSS, and I4.0 with special reference to automation in the process industry. It also delineates the case study in a phase-wise manner to explore the applicability and relevance of LSS with I4.0. The study is archetype in enabling LSS to a new era, and can act as a benchmark document for academicians, researchers, and practitioners for further research and development.