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1 – 10 of 147
Article
Publication date: 1 October 2018

Manjeet Kharub, Shah Limon and Rajiv Kumar Sharma

The purpose of this paper is to empirically investigate the quality tool’s impact on the effectiveness of the Hazard Analysis and Critical Control Point (HACCP)-based food safety…

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Abstract

Purpose

The purpose of this paper is to empirically investigate the quality tool’s impact on the effectiveness of the Hazard Analysis and Critical Control Point (HACCP)-based food safety system and correlation studies between HACCP effectiveness and business performance in food and pharmaceutical industries.

Design/methodology/approach

A total of 116 survey responses of prominent food and pharmaceutical firms are used to fulfil the aim of this study. The principal component analysis (PCA) method was applied to classify quality tools into a finite number of groups. Further, multiple regression methods are employed to investigate the correlation between HACCP effectiveness and firm’s performance indicators.

Findings

Quality tools are classified into three categories on the basis of their application by using the PCA method: quality tools for hazard identification, quality tools for hazard analysis (QTHA) and quality tools for hazard control. The regression analysis revealed that QTHA has a substantial impact on HACCP objectives (hazard identification, hazard assessment and hazard control). Additionally, the results suggest that the successful implementation of HACCP-based food safety system also delivers a direct influence on the operational and financial performance of the food and pharmaceutical industries.

Originality/value

This paper contributes to the existing body of HACCP knowledge by providing a framework supported by an empirical case study. The case study clustered quality tools into three broad categories related to their application of a HACCP project. Study results can guide and motivate managers to use quality tools with the aim of successful implantation of the HACCP-based food safety system, especially in food and pharmaceutical industries.

Details

International Journal of Quality & Reliability Management, vol. 35 no. 9
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 3 April 2018

Manjeet Kharub and Rajiv Kumar Sharma

The purpose of this paper is to explore the relationship between latent variables, i.e. human resource management (HRM) effectiveness, quality cost (QC), and firm performance (FP…

Abstract

Purpose

The purpose of this paper is to explore the relationship between latent variables, i.e. human resource management (HRM) effectiveness, quality cost (QC), and firm performance (FP) for the successful implementation of quality management (QM) practices in micro, small and medium enterprises.

Design/methodology/approach

The data analysis is accomplished in three steps: in the first step, factor analysis was conducted to extract the latent variables representing key QM practices. In the second step, a descriptive analysis (cross-tabulation) was performed to examine the current situation and association between key QM variables and firm size. In the third step, to test the research hypotheses based on latent constructs, structural equation modelling (SEM) has been used.

Findings

The percent point score shows that there are substantial improvements in all organisational aspects after successful implementation of QM practices. The χ2-test revealed that only three domains namely employee participation, recruitment and retaining and supplier relationship are having a significant variation with respect to the firm size. The SEM results show that HRM effectiveness has a direct and positive relationship with FP, whereas QC has a negative association with HRM effectiveness and FP.

Originality/value

Managers will know which aspect they must consider seeing as an indicator of QM practice in their company(s). Out of the three identified latent constructs first will help to create an efficient human capital, whereas the second will help for addressing extra cost due to poor quality. Finally, the third latent variable will show the effectiveness of these two and will assist in evaluating firm’s performance.

Details

International Journal of Quality & Reliability Management, vol. 35 no. 4
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 5 January 2021

Rajiv Kumar Sharma

As we move up in the supply chain (SC) from retailer to supplier, amplification in the fluctuation of order increased. To minimize this amplification, understanding of key…

Abstract

Purpose

As we move up in the supply chain (SC) from retailer to supplier, amplification in the fluctuation of order increased. To minimize this amplification, understanding of key decision variables which affects the SC is essential. So, in the present work the authors developed a novel approach to examine the structural dependencies among variables responsible for perfect order fulfillment (POF).

Design/methodology/approach

Interpretive structural modeling approach has been used to model the structural relationship among the key SC variables. Further, to study the driver-dependence dynamics among variables MICMAC analysis has been used. In the second phase, the influence of driver variables on the POF is investigated by using fuzzy logic.

Findings

From the results, it is observed that the variables’ delivery time, number of echelons, data accuracy and information sharing have high driving power which may help the organizations to meet challenges offered by POF. The results showed that for POF is said to be at optimum level when the number of echelons should be low and data accuracy should be high, and information sharing among all partners should also be very high.

Research limitations/implications

Research on SC is classified into three categories, i.e. operational, design and strategic. In the present study authors discussed strategic variables responsible for POF which is the main limitation of the study. The work can be extended by including operational and design variables.

Practical implications

POF in SC network is affected by various variables. The in-depth understanding of contextual association among the variables helps the managers to improve the efficiency of the SC and reduce the bullwhip effect across the downstream SC network.

Originality/value

The study presents a hybrid approach to analyze the key POF dimensions, i.e. forecasting, number of echelons, information sharing, cycle time and delivery time, critical to POF in downstream SC network by developing various case settings.

Details

International Journal of Quality & Reliability Management, vol. 38 no. 8
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 9 January 2024

Love Kumar and Rajiv Kumar Sharma

In the context of promoting sustainable development in SMEs, the present study aims to investigate the relationship among solution dimensions based on the Industry 4.0 (I4.0…

Abstract

Purpose

In the context of promoting sustainable development in SMEs, the present study aims to investigate the relationship among solution dimensions based on the Industry 4.0 (I4.0) concept.

Design/methodology/approach

The study employs a comprehensive methodology that includes a systematic literature review, workshop, grounded theory and interpretive structural modeling. Various dimensions concerning I4.0 sustainability are tested and evaluated using a questionnaire design followed by hypothesis formulation. Further, grounded theory is used to extract the key solution dimensions that capture the essence of I4.0 implementation in SMEs. Finally, the solution dimensions for I4.0 sustainability are modeled using the ISM approach to understand the structural interdependencies among them, and Matrice d'Impacts Croisés Multiplication Applied to a Classification (MICMAC) analysis is done to understand the driving and dependence power among these dimensions.

Findings

The study identified 14 solution dimensions for the implementation of I4.0 in SMEs for sustainable development. Out of the 14 solution dimensions, human resource training programs (D4) appear at level 11, followed by top management commitment (D1), strategic collaborations (D3) and coordination among key stakeholders (D5) at level 2 in the hierarchical interpretive structural modeling (ISM) model. Also, these dimensions have an effect size of more than 0.50 which indicates a substantial correlation between the sustainability dimensions and Industry 4.0 implementation in SMEs.

Originality/value

The study contributes to the overall goal of fostering sustainability within the SME sector, which can pave the way for various stakeholders for the successful implementation of I4.0 sustainable solution dimensions.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 29 May 2007

Rajiv Kumar Sharma, Dinesh Kumar and Pradeep Kumar

The aim of this paper is to permit system reliability analysts/managers/practitioners/engineers to analyse system failure behaviour more consistently and plan suitable maintenance…

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Abstract

Purpose

The aim of this paper is to permit system reliability analysts/managers/practitioners/engineers to analyse system failure behaviour more consistently and plan suitable maintenance actions accordingly.

Design/methodology/approach

The paper adopted three important tools, namely, root cause analysis (RCA), failure mode effect analysis (FMEA), and non‐homogeneous Poisson point process (NHPPP), to build an integrated and helpful framework, able to facilitate the maintenance managers in decision making. The factors contributing to system unreliability were analysed using RCA and FMEA. The failure data related to the components are modelled using NHPPP models and are used to optimise maintenance decisions (repair or replacements) based on cost dimensions.

Findings

The paper finds that the in‐depth analysis of a system using RCA and FMEA helps to create a knowledge base to deal with problems related to process/product unreliability. From the results it is observed that NHPPP models adequately analyse time‐dependent rate of occurrence of failures. Thus, assisting the maintenance analyst in development of suitable maintenance strategy by properly understanding the mechanism of failure (through modeling of failure data); adopting adequate aging management actions (such as predictive or periodic testing) to predict or detect the degradation of components; and performing cost analysis.

Originality/value

The contemporaneous adoption of the three proposed techniques for failure analysis will help system reliability engineers/managers/practitioners not only to understand the failure behaviour of component(s) in the system, but also to plan/adapt suitable maintenance practices to improve system reliability and availability.

Details

International Journal of Quality & Reliability Management, vol. 24 no. 5
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 5 June 2007

Rajiv Kumar Sharma, Dinesh Kumar and Pradeep Kumar

This paper aims to permit the system reliability analysts/managers/practitioners/engineers to analyze the system failure behavior using fuzzy methodology (FM)

5512

Abstract

Purpose

This paper aims to permit the system reliability analysts/managers/practitioners/engineers to analyze the system failure behavior using fuzzy methodology (FM)

Design/methodology/approach

In order to deal with both qualitative and quantitative information related to system performance the authors have adopted failure mode effect analysis (FMEA) and Petrinets (PNs), the well‐known tools for reliability analysis, to build an integrated framework aimed at helping the reliability and maintenance managers in decision‐making.

Findings

Using the proposed framework an industrial case from the paper mill is examined. From the results it is observed that the limitations associated with the traditional procedure of risk ranking in FMEA are efficiently modeled using fuzzy decision‐making system (FDMS) based on FM. Also, the fuzzy synthesis of system failure and repair data helps to quantify the system behavior in a more realistic manner.

Originality/value

The simultaneous adoption of the proposed techniques to model, analyze and predict the uncertain behavior of an industrial system will not only help the reliability engineers/managers/practitioners to understand the behavioral dynamics of system but also to plan/adapt suitable maintenance practices to improve system reliability, availability and maintainability (RAM) aspects.

Details

Engineering Computations, vol. 24 no. 4
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 16 January 2007

Rajiv Kumar Sharma, Dinesh Kumar and Pradeep Kumar

The purpose of this paper is to describe a structured framework to implement and sustain a quality costing system (QCS) based on process cost modeling (PCM) in process industries.

1872

Abstract

Purpose

The purpose of this paper is to describe a structured framework to implement and sustain a quality costing system (QCS) based on process cost modeling (PCM) in process industries.

Design/methodology/approach

After reviewing and analyzing various cost accounting methodologies practiced by companies the research objectives were achieved by acknowledging the need to attach fuzziness to notion of “quality”. The imprecise, vague, and complex information related to cost items under Prevention, Appraisal and Failure (PAF) segments is synthesized using well‐established fuzzy principles. A case based approach from process industry is discussed to implement and sustain quality costing system after prioritizing the processes.

Findings

While conforming on the results of prior research on practice of quality costing approaches and the problems faced by the companies in implementing a quality management system the fuzzy approach (owing to its sound logic and effectiveness in identifying the vagueness and imprecision in human judgment) is successfully applied to elicit expert opinion regarding the importance of cost items. The information so obtained after fuzzy synthesis is used to set up priority with respect to the processes which can provide necessary help to managers/practioneners to invest efforts in reduction of cost of non‐conformances (CONC) and optimal allocation of resources.

Practical implications

The approach discussed in the paper will be helpful to managers; quality practitioners to set up/improve various quality improvement initiatives for successful implementation of quality costing system.

Originality/value

The framework discussed in the paper provides a novel approach to implement QCS by using PCM after judicious selection of the processes and cost items.

Details

The TQM Magazine, vol. 19 no. 1
Type: Research Article
ISSN: 0954-478X

Keywords

Article
Publication date: 30 March 2010

Rajiv Kumar Sharma and Pooja Sharma

The purpose of this paper is to permit the system reliability analysts/managers/engineers to model, analyze and predict the behavior of industrial systems in a more realistic and…

3153

Abstract

Purpose

The purpose of this paper is to permit the system reliability analysts/managers/engineers to model, analyze and predict the behavior of industrial systems in a more realistic and consistent manner and plan suitable maintenance strategies accordingly.

Design/methodology/approach

Root cause analysis (RCA), failure mode effect analysis (FMEA) and fuzzy methodology (FM) have been used by the authors to build an integrated framework, to facilitate the reliability/system analysts in maintenance planning. The factors contributing to system unreliability were analyzed using RCA and FMEA. The uncertainty related to performance of system is modeled using fuzzy synthesis of information.

Findings

The in‐depth analysis of system is carried out using RCA and FMEA. The discrepancies associated with the traditional procedure of risk ranking in FMEA are modeled using decision making system based on fuzzy methodology. Further, to cope up with imprecise, uncertain and subjective information related to system performance, the system behavior is quantified by fuzzy synthesis of information.

Originality/value

The complementary adoption of the techniques as discussed in the study will help the maintenance engineers/managers/practitioners to plan/adapt suitable maintenance practices to improve system reliability and maintainability aspects after understanding the failure behavior of component(s) in the system.

Details

Journal of Quality in Maintenance Engineering, vol. 16 no. 1
Type: Research Article
ISSN: 1355-2511

Keywords

Article
Publication date: 29 April 2014

Pratima Mishra and Rajiv Kumar Sharma

The purpose of this paper is to introduce a hybrid framework (suppliers, inputs, process, output and customers+define, measure, analyze, improve and control (SIPOC+DMAIC)) aimed…

6161

Abstract

Purpose

The purpose of this paper is to introduce a hybrid framework (suppliers, inputs, process, output and customers+define, measure, analyze, improve and control (SIPOC+DMAIC)) aimed at improving supply chain management (SCM) process dimensions in a supply chain (SC) network.

Design/methodology/approach

Based upon the critical review of literature, process dimensions (average outgoing quality limit (AOQL), average outgoing quality (AOQ), process Z, defect per million opportunity) critical to SCM performance were identified. A framework consisting of three phases, i.e., design, implementation and results has been conceptualized and a case from paint industry is investigated. Implementation framework makes use of SIPOC model and Six Sigma DMAIC methodology. The goals of the study were achieved by using Six Sigma tools such as brainstorming sessions; root cause analysis, histograms, statistical tools such as control charts and process capability analysis.

Findings

Authors made an attempt to propose a conceptual framework for improving process dimensions in a SC network. It is observed from the results that selection of appropriate strategies for improving process performance based upon experiences, and use of statistical tools by cross-functional teams with an effective coordination, guarantees success. Metrics such as AOQL shows the maximum worst possible defective or defect rate for the AOQ. Process Z helps to know about sigma capability of the process.

Research limitations/implications

The framework so developed is tested in a single company manufacturing batches of paint. The study has important implications for the industry since it tries to integrate SCM process dimensions which would help in successful implementation of SCM practices in firm by following the DMAIC process. The framework enables the practitioners to investigate the process and demonstrate improvements using DMAIC which makes use of statistical tools.

Originality/value

Although process dimensions related to SCM are critical to organization competitiveness, research so far has tended to focus on supply chain operations and reference model, balanced scorecard, total quality management, activity-based costing, just in time, etc., but in literature hardly any description of the SIPOC-DMAIC model to improve SCM process performance is provided. The use of statistics in DMAIC provides better insight into the process performance, and process control.

Details

International Journal of Quality & Reliability Management, vol. 31 no. 5
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 1 December 2005

Rajiv Kumar Sharma, Dinesh Kumar and Pradeep Kumar

To help the maintenance managers/decision makers to select a suitable maintenance strategy for the components/parts associated with the system.

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Abstract

Purpose

To help the maintenance managers/decision makers to select a suitable maintenance strategy for the components/parts associated with the system.

Design/methodology/approach

An approach based on fuzzy linguistic modeling is used to select the most effective and efficient maintenance strategy. Three input parameters, i.e. historical data (I1), present data (I2) and competence of data (I3) related to failures of a component (gears), were taken to judge the effectiveness of the nature of maintenance strategies. These parameters are represented as members of a fuzzy set, combined by matching them against (if‐then) rules in rule base, evaluated in fuzzy inference system (Mamdani, min‐max type) and then defuzzified to assess the capability or effectiveness of maintenance strategy.

Findings

The results show how the fuzzy logic approach translates vague, ambiguous, qualitative and imprecise information into numerical/quantitative terms, which helps to identify the most informative and efficient maintenance strategy. From the computed performance index values for each maintenance strategy it is observed that proactive (CBM) and aggressive maintenance strategy (TPM) are far better compared with traditional, reactive (BDM) maintenance strategy.

Originality/value

The paper integrates fuzzy logic modeling – a knowledge‐based approach with database obtained through maintenance logs, historical records, equipment manuals and expert judgement, which might prove beneficial for maintenance managers/engineers/practitioners to select a suitable maintenance strategy for each piece of equipment associated with the systems.

Details

Journal of Quality in Maintenance Engineering, vol. 11 no. 4
Type: Research Article
ISSN: 1355-2511

Keywords

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