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Article
Publication date: 5 June 2017

Karthik Bharathi S., S. Vinodh, Sriharsha Devarapu and Goutham Siddhamshetty

The purpose of the study reported in the paper is to apply a structured problem-solving approach based on the Lean approach to analyse weld defects and derive appropriate…

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Abstract

Purpose

The purpose of the study reported in the paper is to apply a structured problem-solving approach based on the Lean approach to analyse weld defects and derive appropriate solutions.

Design/methodology/approach

Manufacturing organisations involved in welding fabrication are expected to reduce weld defects to attain competitive advantage. Weld defects need to be systematically analysed for valve performance enhancement. In this research study, Lean approach is used to reduce variations and waste by annihilating the root causes for failures that occur during submerged arc welding (SAW) process.

Findings

The deployment of solutions facilitated weld defect reduction and substantial financial savings for the organisation.

Research limitations/implications

The framework has been test-implemented for analysing variations and wastes generated in the SAW process. In future, studies could be conducted for assessing different welding processes.

Practical implications

The proposed Lean framework has been successfully implemented in a large-scale manufacturing unit involved in fabrication work.

Originality/value

Lean framework has been test-implemented in a large-scale manufacturing organisation involved in weld fabrication work.

Details

International Journal of Lean Six Sigma, vol. 8 no. 2
Type: Research Article
ISSN: 2040-4166

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Article
Publication date: 18 September 2019

Nilda Tri Putri and Lora Seprima Dona

The purpose of this paper is to redesign the layout of production floor by considering lean manufacturing in order to eliminate the waste and using Block Layout Overview with…

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Abstract

Purpose

The purpose of this paper is to redesign the layout of production floor by considering lean manufacturing in order to eliminate the waste and using Block Layout Overview with Layout Planning (BLOCPLAN) algorithm to attain new layout of facilities in Indonesian home-food industry.

Design/methodology/approach

The common problems that might be appearing in home-food industry, especially in the developing countries like Indonesia are unstandardized production process and unorganized work environment which could produce the waste. One of many solutions to handle this problem is improving the work area (work station) in production floor by rearranging and designing standard operating procedure (SOP) by using lean manufacturing concept. The initial data to minimize the waste is motion time study (data) to identify production standard time. The next step is identifying the common waste(s). Meanwhile, the production floor layout used in this research is designed by using BLOCPLAN algorithm.

Findings

The recommendation of shop floor facility layout is based on identified waste, which is excess transportation. Subsequently, standard operational procedure (SOP) is developed to support the recommended facility layout as the reference for cookie production process so it can minimize the waste.

Research limitations/implications

Lean concept is one of method that is widely implemented to reduce the occurrence of defective products and waste that do not provide added value. Based on previous researches, it was found that the concept of lean manufacturing can be applied in various types of service and manufacturing industries, both large companies and small and medium enterprises. Home-food industry competition nowadays is getting intense. This condition makes the stakeholders (of home-food industry, especially in Indonesia) need high performance and productivity to keep their business stable in winning the competition. The new layout can reduce the disadvantages of actual condition.

Practical implications

This research is useful for small- and medium-sized enterprises (SMEs) in Indonesia especially for home-food industry. The BLOCPLAN layout (as the recommendation) has displacement moment with reduction of 40 percent.

Social implications

This research believed that it can help SMEs improve their productivity in producing cake and cookies in terms of better layout which can reduce worker movement and standardized working procedure. The design of the production facility layout is a method used to rearrange the production process area so that the distance between processes can be minimized. SOPs was provided as the direction and supervision of workers to work according to standards.

Originality/value

SOP design can support recommended layout as the reference on making the cake (product) to eliminate wastes, which are motion/movement (alternating in production process flow) and long waiting time due to process delays.

Details

The TQM Journal, vol. 31 no. 5
Type: Research Article
ISSN: 1754-2731

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Article
Publication date: 9 December 2024

Sufyan Sikander, Afshan Naseem, Asjad Shahzad, Muhammad Jawad Akhtar and Ali Salman

In recent years, especially after the COVID-19 pandemic, home textile production orders decreased significantly. This sudden drop in production has increased industry competition…

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Abstract

Purpose

In recent years, especially after the COVID-19 pandemic, home textile production orders decreased significantly. This sudden drop in production has increased industry competition, making customer satisfaction more challenging. As a result, it has become imperative for the industry to deftly navigate such ongoing challenges.

Design/methodology/approach

This study examines textile production efficiency methodically. Customer requirements like quality, on-time delivery, better working conditions, cost-effectiveness and facility safety audits are understood first. Quality function deployment (QFD) turns client requirements into technical requirements. Prioritise and analyse risks using Monte Carlo simulation and Pareto charts. Consequently, experts and literature propose corrective measures, which are tested in a pilot run to see how they affect production.

Findings

QFD, define, measure, analyse, improve and control (DMAIC) and Monte Carlo simulation were used to reduce high-priority risks and meet client requirements in this study. The house of quality helped relate customers’ requirements and technical requirements. Monte Carlo simulation has also improved risk prioritisation by providing a flexible mathematical structure for identifying and managing the most important risks.

Originality/value

This study is novel in the way it applies this integrated approach to the understudied home textile sector. Unlike traditional DMAIC, this study introduces a novel matrix encompassing all defects. This study offers a data-driven approach to improve product quality, meet customer expectations and reduce prioritised risks in home textile manufacturing.

Details

International Journal of Productivity and Performance Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1741-0401

Keywords

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Article
Publication date: 16 October 2018

Nandkumar Mishra and Santosh B. Rane

The purpose of this technical paper is to explore the application of analytics and Six Sigma in the manufacturing processes for iron foundries. This study aims to establish a…

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Abstract

Purpose

The purpose of this technical paper is to explore the application of analytics and Six Sigma in the manufacturing processes for iron foundries. This study aims to establish a causal relationship between chemical composition and the quality of the iron casting to achieve the global benchmark quality level.

Design/methodology/approach

The case study-based exploratory research design is used in this study. The problem discovery is done through the literature survey and Delphi method-based expert opinions. The prediction model is built and deployed in 11 cases to validate the research hypothesis. The analytics helps in achieving the statistically significant business goals. The design includes Six Sigma DMAIC (Define – Measure – Analyze – Improve and Control) approach, benchmarking, historical data analysis, literature survey and experiments for the data collection. The data analysis is done through stratification and process capability analysis. The logistic regression-based analytics helps in prediction model building and simulations.

Findings

The application of prediction model helped in quick root cause analysis and reduction of rejection by over 99 per cent saving over INR6.6m per year. This has also enhanced the reliability of the production line and supply chain with on-time delivery of 99.78 per cent, which earlier was 80 per cent. The analytics with Six Sigma DMAIC approach can quickly and easily be applied in manufacturing domain as well.

Research limitations implications

The limitation of the present analytics model is that it provides the point estimates. The model can further be enhanced incorporating range estimates through Monte Carlo simulation.

Practical implications

The increasing use of prediction model in the near future is likely to enhance predictability and efficiencies of the various manufacturing process with sensors and Internet of Things.

Originality/value

The researchers have used design of experiments, artificial neural network and the technical simulations to optimise either chemical composition or mould properties or melt shop parameters. However, this work is based on comprehensive historical data-based analytics. It considers multiple human and temporal factors, sand and mould properties and melt shop parameters along with their relative weight, which is unique. The prediction model is useful to the practitioners for parameter simulation and quality enhancements. The researchers can use similar analytics models with structured Six Sigma DMAIC approach in other manufacturing processes for the simulation and optimisations.

Details

International Journal of Lean Six Sigma, vol. 10 no. 1
Type: Research Article
ISSN: 2040-4166

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