Dr. Saleeshya P. G.

Objective: The aim of the study is to quantify the determinants of hospital performance indicators from a patient’s perspective based on two parameters – patient safety and satisfaction.

Methods: A qualitative and quantitative assessment was done using questionnaires and semi-structured interviews that occurred over a period of eight consecutive weeks. A system dynamics model of the hospital was developed incorporating the determinants of the two significant hospital performance indicators which are patient satisfaction and safety.

Results: The model developed dynamically quantifies the patient satisfaction and safety level upon variation in the model parameters. This has managerial implications on effective capacity utilization within the premises based on supply and demand. The model addresses the problem of aggregate waiting time in hospitals which is a major cause of dissatisfaction among patients in India.

Conclusion: Our model depicts a hospital functioning in a specialty cluster in India, with modest resources and is exposed to similar risks as in our model. The use of electronic medical records data and analytics are not considered in the model as those are still in the infancy stage in most of the government and private run hospitals in India and major improvements are needed to generate new insights and to have an impact on performance measurement.

Originality: The development of a unique comprehensive model for measuring patient satisfaction and safety in a healthcare facility considering the possibilities of risks and related occurrences contributes to the research in healthcare sector.

Lean transformation has already been in use in the manufacturing sector has gained wide acceptance in service sector. Indian economy heavily depends on its service sector. Preliminary study conducted in this sector revealed the emergence of e-commerce has badly affected certain services of the postal systems. So, we felt ahead to assess its performance efficiency. A detailed survey based on specific questionnaires was conducted among employees as well as customers in post offices located in South India. Simultaneously, a field study was done covering various banking systems and courier services. Based on studies and related literature reviews, we developed a new system-based model christened objectivated lean attainment model (OLAM) to assess the performance of postal systems through lean initiatives. Analytical hierarchy process (AHP) is identified to prioritise factors across different levels of the model. The findings and analysis reveals many important aspects which will enable Indian postal system to provide consistent performance index.

This paper is an outcome of a study carried out in a brake manufacturing company in India. The objective of this paper is to strengthen the financial supply chain by eliminating the non-value added elements. Value stream mapping has been used to eliminate the non-value added processes which reduced the production lead time. Based on our inventory analysis, financial ratios were obtained and further analysed to bring out the performance indicators, thus enabling us to improve the overall efficiency of the supply chain. The 0-1 knapsack methodology enabled us to optimise the value of goods flowing through the processes with outputs showing a commendable increase in the financial chain of the process. Finally, we have developed a data envelopment analysis model which helps companies to have better insight and to prioritise its units for effective deployment of resources amongst various units so as to increase its efficiency to maximum level. Copyright © 2019 Inderscience Enterprises Ltd.

Purpose: Lean implementation is a strategic decision. The capacity of organisation to be “Lean” can be identified before lean implementation by assessing leanness of an organisation. This study aims to attempt developing a holistic leanness assessment tool for assessing organisational leanness. Design/methodology/approach: A neuro-fuzzy leanness assessment model for assessing the leanness of a manufacturing system is presented. The model is validated academically and industrially by conducting a case study. Findings: Neuro-fuzzy hybridisation helped assess the leanness accurately. Fuzzy logic helped to perform the leanness assessment more realistically by accounting ambiguity and vagueness in organisational functioning and decision-making processes. Neural network increased the learning capacity of assessment model and increased the accuracy of leanness index. Research limitations/implications: The industrial case study in the paper shows the results in telecom equipment manufacturing industry. This may not represent entire manufacturing sector. The generic nature of the model developed in this research ensures its wide applicability. Practical implications: The neuro-fuzzy hybrid model for assessing leanness helps to identify the potential of an organisation to become “Lean”. The organisational leanness index developed by the study helps to monitor the effectiveness and impact of lean implementation programmes. Originality/value: The leanness assessment models available in literature lack depth and coverage of leanness parameters. The model developed in this research assesses leanness of an organisation by accounting for leanness aspects of inventory management, industrial scheduling, organisational flexibility, ergonomics, product, process, management, workforce, supplier relationship and customer relationship with the help of neuro-fuzzy hybrid modelling. © 2019, Emerald Publishing Limited.

The concept of lean is ever-expanding and has continuously been researched upon. But, the question of how lean a system is has been frequently overlooked. In this study, we have researched upon the capability of a multi-level model to calculate the leanness of a system based on studies conducted in various manufacturing industries. The major issue studied and addressed in the problem is the evaluation of wastes in the system through the inhibitors of lean manufacturing in an industry. The different levels of the assessment model deal with the lean dimensions in the first and topmost level, the eight major wastes in lean manufacturing in the second level and the inhibiting factors affecting lean behaviour in the final level. Leanness as a metric is then calculated through the implementation of variability source mapping and data envelopment analysis techniques on the specific data collected through our research instrument. The obtained results have been assessed through plotting all dimensions simultaneously on a radar chart for evaluation. The results have been presented and the model's validity has been assessed. Inferences were drawn from findings of the study.

Companies worldwide have now realised that ‘customer focus’ is what wins the game. As demands of the customer become more and more volatile and unpredictable, they have to stay ahead of their competitors in fulfilling the needs of the customer. The supply chain as a ‘unit’ has to compete against other supply chains for reaching out and delighting the customer. Responding fast to the changing customer needs has been an intangible factor underlying a successful business. Thus, responsiveness of the supply chain has become the differentiator between the competing supply chains. In this paper, the end-to-end supply chain factors influencing responsiveness are identified from extant literature and a model of responsiveness of the supply chain has been developed by conducting a survey of 204 pump manufacturers. The developed model has been validated through confirmatory factor analysis using structural equation modelling. These findings can help to identify the areas of improvement for the supply chain and may lead to a focused improvement in these areas thus improving responsiveness and profitability.

During emergencies, decision making to support relief preparedness and response activities are challenging task requiring quick and effective action from responders under uncertainty conditions. This paper proposes a response planning stochastic model for humanitarian transportation operations. The objective of this proposed model is to minimise total transportation duration during emergency situations. This model aims to maximise satisfaction levels through attaining quick response which can help in making decisions on disaster relief logistics. © Copyright 2016 Inderscience Enterprises Ltd.

In this study, we concentrate on one of the three major areas of the whole transit network design problem that being the frequency setting. The main problem addressed here is the minimisation of losses borne by a public state transport corporation in India. This is achieved by optimally allocating resources to shared routes already in existence. The bus frequency setting problem is solved using a bi-level methodology. In the first level minimum required fleet size for the routes are found out by considering the routes individually. In the second level with the guarantee of load feasibility, allocation of frequencies is done for the fleet size found in the first level. This is done by also taking into consideration the achievement of minimisation of operational cost of the routes under consideration as added objectives. The relation between the operations cost and the maintained frequencies are found out using artificial neural network (ANN), and the second level is solved using a multi objective genetic algorithm (GA). This methodology has been used in optimising two shared routes and the results are thus presented.

Lean manufacturing is an emerging concept in the Indian manufacturing scenario. Many small and medium scale enterprises in the country are aiming at becoming lean and thereby improving their productivity. This paper is an outcome of a case study in one such enterprise that deals with the manufacturing and assembly of offset printing machinery in India. Being a vendor-based organisation, part shortage due to delays in the process was a major problem faced. A thorough analysis of the various vendors and processes that the product goes through was done and the process flow was mapped to obtain a clear picture of the entire system, and software modelling helped arrive at quantitative results. Lean tools like Pareto analysis, five-why analysis, source inspection, etc., were used to identify and eliminate the various factors that led to delay. Proper scheduling of jobs is also essential to reduce waiting time, and therefore an algorithm has been developed to help arrive at an optimum scheduling sequence. The results from this case study have proved successful in reducing the lead time of the component under study. Copyright © 2015 Inderscience Enterprises Ltd.

This paper is related to a real life study carried out in Indian manufacturing organisations to assess the extent to which the agile manufacturing paradigm is recognised and deployed, as this paradigm has been a major objective of many companies. A multi-level framework developed by the authors, along with a questionnaire was used to identify various enabling factors of agility in Indian manufacturing industries. This model helps to determine the measure of agility called ‘Effectiveness Index’ (EI) at the various hierarchical levels of an organisation. In this paper we propose an approach to measure the agility of manufacturing systems by combining the analytical hierarchy process (AHP) and the data envelopment analysis (DEA) methodologies. The method of AHP was used to identify important agility enablers by deriving appropriate weights (Importance Index). DEA was used to compare and find out the priorities of various units of organisations by making use of the values of EI and Importance Index for agility.

Lean manufacturing is a philosophy of eliminating waste through continuous improvement. This paper is an outcome of a case study conducted in a textile industry in south India. Though the concept of lean manufacturing has shown good results in continuous process industry, it has not been extensively used as compared to discrete manufacturing industries. Process industries, especially textile industries, have automatic machinery which are highly inflexible and have high volume/low variety products. This nature of the textile industry makes implementing lean manufacturing techniques a challenge; hence implementing lean techniques in a textile industry has been taken up as a challenge. We have chosen a combination of value stream mapping (VSM), 5S, kanban, kaizen, poka-yoke, and visual controls to improve the processes. The achievement potential scores before and after lean implementation has been highlighted using radar diagrams. The findings of this study reveal that a thorough analysis of the process, setup, and changeover time (CO), use of colour coding for identification of volume-mix, use of kaizen and quality circles which empower the workforce, are some of the various keys to a successful lean implementation in a textile industry.

Today's manufacturing companies are measured by how fast they meet the customer and user requirements, how responsive they are to the changing market demands and how capable they are in producing good quality products and supply them at optimal cost. Lean manufacturing is a manufacturing concept which has demonstrated results of successful implementation especially in discrete manufacturing companies. This paper presents a case study of an Indian pharmaceutical firm to outline the scope of a successful lean based manufacturing strategy implementation in this sector. Analytic Network Process (ANP) is applied to measure and rate the present leanness of a pharmaceutical firm. A multi-level model along with the questionnaires developed by the authors was used for the initial assessment. The approach helped to assess the current leanness level. Since inhibitors for lean interventions were identified the authors studied them and established the correlation among different parameters using Interpretive structural modelling (ISM) approach. The model was also validated through MICMAC analysis. The results of ANP, ISM and MICMAC showed the root causes for the unsuccessful implementation of lean in the firm. They were the lack of a responsive supply chain and the excessive Quality regulations and enforcements by the Authorities. This study gives guidelines to companies planning for lean implementation to deploy methods to remove the inhibitors of lean at the initial stages. Identifying the barriers can guide managers in developing strategies to eliminate them at the inception. This paper recommends supplier qualification programmes which managers can use to get the suppliers be part of their extended lean family. Through this supplier's involvement can be improved with an aim of improving the product lead time. © Published under licence by IOP Publishing Ltd.