This paper deals with concept of total productive maintenance (TPM) and its implementation approach. It also presents the identification of critical factors for effective implementation of TPM. The reliability analysis identified potential areas where more concentration is required. The application of hypothesis testing in productivity maintenance should be promoted by parametric test and significantly instrumental in explanation of phenomena. It is also indispensable to better understand quality data and provide guidance to production control.
The various critical success factors of TPM implementation has organised into set of eight performance measure and thirty three sub-factors for getting the in-depth details of each indicator. The paper identifies the reliability of these factors and understands the problem with greater clarity and its ramification. Researcher collected responses from forty one manufacturing organisations through structured designed questionnaire. The reliability analysis was carriedout by calculating the value of Cronbach's alpha method. To draw the meaningful conclusions supported by relevant empirical data, provisional formulation is required, and it was carried by hypothesis testing. In this test, samples are taken from a population with known distribution (normal distribution), and a test of population parameters is executed. It determines the relevancy of facts directs the researcher's efforts into productive channels. The statements were hypothetically tested by calculating the arithmetic value of Chi-Square (χ2) and MINITAB-19 software was used for identification of p-value.
This study identified that main factors and sub-factors of TPM which are critical for implementation of TPM. The study also avoids the complexities involved in implementing TPM by reliability analysis. It is found that all identified CSFs are reliable as Cronbach's alpha is above 0.6. The hypothesis testing shows that all alternative hypothesis statements are acceptable as Chi-Square (χ2) value has satisfied the conditions and null hypothesis are true as calculated p-value is less than the 0.05 for eight identified TPM critical factor.
In this paper researcher provides a comprehensive typology of TPM-CSFs, and its ranking and importance in manufacturing sector. The preparedness of such study related to TPM implementation is becoming a major sourcing base for the world and there is a paucity of such studies. Such studies are equally important in a global context.
The authors are thankful to all the industrial participants for their valuable input and support for the collection of data through the structured questionnaire.
Kalpande, S.D. and Toke, L.K. (2022), "Reliability analysis and hypothesis testing of critical success factors of total productive maintenance", International Journal of Quality & Reliability Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJQRM-03-2021-0068
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