Pradip Kumar Ray

A review of optimization techniques in metal cutting processes

In todays rapidly changing scenario in manufacturing industries, applications of optimization techniques in metal cutting processes is essential for a manufacturing unit to respond effectively to severe competitiveness and increasing demand of quality product in the market. Optimization methods in metal cutting processes, considered to be a vital tool for continual improvement of output quality in products and processes include modelling of input-output and in-process parameters relationship and determination of optimal cutting conditions. However, determination of optimal cutting conditions through cost-effective mathematical models is a complex research endeavour, and over the years, the techniques of modelling and optimization have undergone substantial development and expansion. In this paper, the application potential of several modelling and optimization techniques in metal cutting processes, classified under several criteria, has been critically appraised, and a generic framework for parameter optimization in metal cutting processes is suggested for the benefits of selection of an appropriate approach.

Patient flow modelling and performance analysis of healthcare delivery processes in hospitals

Modelling patient flows, important for performance improvement of hospital processes.Existing approaches for patient flow modelling in hospital systems are classified.Recent literature on patient flow modelling and performance analysis is reviewed.A generic framework for such modelling and analysis of hospital systems is provided.The framework may serve as a guide to improve healthcare delivery. Analysis of hospital processes is essential for development of improved methods, policies and decision tools for overall performance improvement of the hospital system. Amidst the current scenario of continuously increasing healthcare costs and scarcity of resources, optimal utilization of resources without hampering the quality of care has gained importance in any country. Modelling, analysis and management of patient flows, in this context, plays a key role in performance analysis and improvement of hospital processes as appropriate modelling of patient flows may help healthcare managers make decisions related to capacity planning, resource allocation and scheduling, appointment scheduling and for making necessary changes in the process of care. The concept of patient flow and its modelling has gained much attention in healthcare management literature over past few decades. In this paper, the existing approaches pertaining to modelling of patient flows in hospital systems have been classified and critically appraised focussing on the recent advancements in order to identify future research avenues. A generic framework for patient flow modelling and performance analysis of hospital systems that may serve as a guide for the practitioners dealing with similar kinds of problems to improve healthcare delivery has also been provided.

Optimal process design of two-stage multiple responses grinding processes using desirability functions and metaheuristic technique

Two-stage grinding processes in mass-scale manufacturing unit are usually too complex to optimize, due to large number of interacting process variables, between and within the stages. Furthermore, statistical design of experiment techniques, such as factorial design, fractional factorial and response surface design by sequential experimentations, to determine the exact optimal process design for the overall interdependent two-stage system, are sometimes too difficult to implement, if not impossible. In this context, considering each stage in isolation and determining individual optimal conditions may not result in an optimal process design, when the entire two-stage system is considered. The aim of this study is to apply empirical modelling technique based on direct observations, for prediction of a two-stage grinding process behaviour having multiple response characteristics of continuous variables, and determine overall optimal process design to meet the specific customer requirements. In order to achieve the above goal, the study proposes an integrated approach using multivariate regression, desirability function, and metaheuristic search technique. Three different metaheuristic search techniques, viz. real-coded genetic algorithm, simulated annealing, and a modified Tabu search based on novel Mahalanobis multivariate distance approach to identify Tabu moves, are employed to determining near optimal path conditions for an industrial case study of two-stage CNC grinding (honing) optimization problem, having various process and variable constraints. Computational study results based on different metaheuristics, and applied on the same two-stage optimization problem, show that the modified Tabu search performs better and also offer opportunities to be extended for other multi-stage metal-cutting process optimization problems.

Productivity Management in India: A Delphi Study

Concepts underlying productivity management and other measures of organisational performance are discussed. Expert opinions can clarify many “misunderstood” concepts which need an interdisciplinary approach for exploration. The Delphi technique, as a structured group communication process employing the group process or participative approach, has been recommended with a view to formulating appropriate policies. Four issues, namely organisational objectives related to productivity improvement, productivity measures, problems faced in implementing productivity improvement techniques or tools, and recommendations to overcome the problems in manufacturing organisations in India are extensively investigated through a Delphi study, conducted during 1987‐88.

The Measurement and Evaluation of White‐collar Productivity

Critical analysis of previously developed white‐collar productivity management techniques focuses on the existing shortcomings of several measurement and evaluation methodologies of white‐collar personnel and functions. An analytical method of defining and measuring various pertinent characteristics of both routine and non‐routine white‐collar jobs helps in the development of a more suitable productivity management methodology. A systematic procedure is described for the measurement and evaluation of white‐collar productivity for an individual, a group of individuals or a department. The recommended measures, viz, operations‐based productivity measures for routine and non‐routine jobs, explain in detail the relationship of different white‐collar job characteristics and individual and group productivity at the middle management level. A case example is cited which illustrates the proposed approach. The advantages, along with some limitations, of the methodology are also highlighted.

Modelling robustness for manufacturing processes: a critical review

‘Robustness’ is an important concept used in quality engineering for the improvement of quality in a manufacturing process. A process which is insensitive to noise variation is called a robust process. The robustness is modelled by several researchers and practioners for its design and implementation in a manufacturing process. A review of all these approaches is essential in order to assess their strengths, limitations and applicability under different process conditions and constraints. Over the years, many of these approaches have found widespread application in measuring, assessing and modelling of process robustness in manufacturing and other industries. In this paper, an attempt has been made to review critically the existing approaches as proposed and applied for measuring and evaluating robustness of manufacturing processes. Based on the critical appraisal, the key issues are identified and a generic framework for modelling and measuring of process robustness in single- and multi-stage manufacturing processes is presented.

Interpretive structural modelling for critical success factors of R&D performance in Indian manufacturing firms

Purpose – In order to enhance the performance of R&D in manufacturing organizations, the R&D managers need to identify the internal as well as the external factors that affect the R&D performance of manufacturing organizations in India. They need to understand the inter‐dependencies of these factors. This paper seeks to identify the critical success factors for R&D in Indian manufacturing firms.Design/methodology/approach – There may be a number of factors that are critical for achieving acceptable R&D performance and these factors have been identified by a number of instruments or means, such as questionnaire surveys, brainstorming, and consolidation by Principal Component Analysis (PCA). A total of 14 factors have been identified by using principal component analysis and finally we have developed a structure of interrelationship among the identified critical success factors using an interpretive structural model.Findings – The results show that R&D vision and direction and R&D oriented culture are the m...

Quality improvement of multistage and multi-response grinding processes: an insight into two different methodologies for parameter optimisation

Process quality improvement using appropriate optimisation methodology has been a continual research endeavour. However, search for optimal path conditions for multi-stage and multi-response grinding in mass-scale manufacturing still remains a critical and difficult task for researchers. In this context, two different methodologies may be adopted to determine optimal process setting conditions. The first methodology (Methodology-1) is to assume each stage as independent, and thereby determine optimal setting conditions for the individual stages. Based on individual stage optimal process conditions, overall optimal path conditions are selected. Another possible methodology (Methodology-2) for optimisation is to consider all the stages as a single system, with their interdependency, and thereby determine the overall optimal path conditions. In this paper, an attempt has been made to compare and contrast the solution quality, as determined by genetic algorithm, and tabu search for both the methodology. The computational results show the relative superiority of tabu search.

Flexibility and performance relationships: evidence from Indian bearing manufacturing firm

The objective of the research study is to establish a relationship between flexibility and performance in production systems. To explore the relationship in real life data, a case study was conducted at a leading bearing manufacturing firm in India. The firm produces bearing for automotive manufacturers. Product quality and production system performance in a firm found to be important for issues concerning manufacturing flexibility. The study in particular discusses the manufacturing strategy prevailing in the firm. Empirical relationships are established relating flexibility and performance. Path values between the factors (flexibility-performance) for all feasible part-machine combinations are calculated. The study reports the critical findings while relating these two factors. The findings have implications for both manufacturers as well as researchers.

Modelling robustness in serial multi-stage manufacturing processes

The study of robustness in single-stage manufacturing has been explored by a large number of researchers and practitioners. However, modelling of robustness in multi-stage manufacturing using multivariate data is seldom used. The aim of this paper is to develop a methodology to model process robustness in a serial multi-stage manufacturing system. Combining statistical regression, Taylor series expansion, the root-sum-squares method and a variation model, the methodology proposes a measurement system for robustness. The resulting metric, while quantifying robustness, measures absorbed and transmitted variations across the stages of a manufacturing process. Using the methodology in a serial two-stage worm gear manufacturing process, the levels of robustness and both absorbed and transmitted variations are determined, thus identifying significant variations across manufacturing stages. The details of this application with the types of corrective actions as required for minimisation of process performance deterioration are presented.