Makarand S. Kulkarni

Combined Taguchi and dual response method for optimization of a centerless grinding operation

Abstract Offline quality control has been widely accepted as a key to high quality products at low price. The concept of robust design using Taguchi methodology is versatile and its application is not limited to any specific area. However, Taguchi techniques have their own shortcomings. Other methodologies like dual response methodology for process optimization have also been used with success. This paper presents a successful application of combined Taguchi and dual response methodology to determine robust condition for minimization of out of roundness error of workpieces for centerless grinding operation. From the confirmation runs, it was observed that this approach led to successful identification of optimum process parameter values.

A methodology for joint optimization for maintenance planning, process quality and production scheduling

Performance of a manufacturing system depends significantly on the shop floor performance. Traditionally, shop floor operational policies concerning maintenance scheduling, quality control and production scheduling have been considered and optimized independently. However, these three aspects of operations planning do have an interaction effect on each other and hence need to be considered jointly for improving the system performance. In this paper, a model is developed for joint optimization of these three aspects in a manufacturing system. First, a model has been developed for integrating maintenance scheduling and process quality control policy decisions. It provided an optimal preventive maintenance interval and control chart parameters that minimize expected cost per unit time. Subsequently, the optimal preventive maintenance interval is integrated with the production schedule in order to determine the optimal batch sequence that will minimize penalty-cost incurred due to schedule delay. An example is presented to illustrate the proposed model. It also compares the system performance employing the proposed integrated approach with that obtained by considering maintenance, quality and production scheduling independently. Substantial economic benefits are seen in the joint optimization.

Joint consideration of production scheduling, maintenance and quality policies: a review and conceptual framework

Performance of a manufacturing system depends on its ability to simultaneously meet several requirements such as: quick response to market demand, high product quality, low manufacturing costs and timely deliveries; which in turn strongly depend on performance at the shop floor level. In the past, the shop floor level operational policies in the context of scheduling, maintenance and quality have been examined in isolation. However, it is hypothesised that these three aspects of operations planning may also have some interaction effect and hence joint consideration of various policy options pertaining to quality, maintenance and scheduling on the performance of the manufacturing system is an important area for investigation. In this paper, a review of literature addressing the joint consideration of these three aspects is presented and research gaps are highlighted. As a preliminary work, some numerical investigations are also presented to highlight the importance of joint consideration of these three aspects. Finally, a conceptual methodology is presented that can lead to further developments in this field. Some potential research areas in this context are identified.

Optimal maintenance schedule decisions for machine tools considering the user's cost structure

This paper proposes a model for obtaining optimal preventive repair and replacement intervals of a machine tool subassembly considering the users cost structure and the effect of major overhauls. Corrective actions are considered as minimal, whereas preventive repair and major overhauls are considered as imperfect in this paper. The objective is to obtain optimal repair/replacement decisions for the machine tool subassembly such that the expected life-cycle cost contribution over the whole life of the system is minimised. The proposed strategy improves over other existing strategies since it simultaneously considers the effects of the users cost structure and major overhauls, while optimising the preventive repair and replacement intervals. A numerical illustration is provided to demonstrate the general application of the proposed approach.

Integrated reliability and optimal maintenance schedule design : a Life Cycle Cost based approach

Customers of industrial system/machines are becoming increasingly focused on life cycle performance of products for their purchase decisions. Manufacturers of such type of products, for example machine tools, are experiencing increased pressure from customers to deliver customised products with documented reliability, maintainability, maintenance and support characteristics and also with minimum environmental impacts. In this article, first the problem has been explored in the context of Indian machine tool industry and also from literature perspective. Some of the important issues are listed and research steps are identified to address these issues.

A parameter estimation method for machine tool reliability analysis using expert judgement

This paper aims at providing a parameter estimation method for the machine tool reliability analysis to overcome the problem of unavailability of a well-defined failure data collection mechanism. It uses the knowledge and experience of maintenance personnel to obtain the parameters of lifetime distribution of the repairable as well as non-repairable components/subassemblies. It is further developed for the cases where the knowledge available with the expert is with reference to the preventive repair/replacement policy used in the field. In case of imperfect repairs, the methodology also helps in estimating the value of restoration factor. The goodness of the proposed methodology at a given accuracy level in expert judgements are tested against the maximum likelihood estimates of the parameters. It is concluded that the expert judgement method provides a satisfactory alternative to statistical methods when no or very few historical time to failure data points are available.

A methodology for simultaneous optimisation of design parameters for the preventive maintenance and quality policy incorporating Taguchi loss function

The performance of a production system depends on the breakdown-free operation of equipment and processes. Maintenance and quality control play an important role in achieving this goal. In addition to deteriorating with time, equipment may experience a quality shift (i.e. process moves to out-of-control state), which is characterised by a higher rejection rate and a higher tendency to fail. This paper develops an integrated model for joint optimisation of preventive maintenance interval and control parameters incorporating the Taguchi loss function. We consider two types of maintenance policies: minimal corrective maintenance that maintains the state of the equipment without affecting the age and imperfect preventive maintenance that upgrades the equipment in between ‘as good as new’ and ‘as bad as old’ condition. The proposed model enables the determination of the optimal value of each of the four decision variables, i.e. sample size (n), sample frequency (h), control limit coefficient (k), and preventive maintenance interval (t PM) that minimises the expected total cost of the integration per unit time. A numerical example is presented to demonstrate the effect of the cost parameters on the joint economic design of preventive maintenance and process quality control policy. The sensitivity of the various parameters is also examined.

Optimal Reliability Design of a System

Reliability is one of the most important attributes of performance in arriving at the optimal design of a system since it directly and significantly influences the system’s performance and its life cycle costs. Poor reliability would greatly increase life-cycle costs of the system, and reliability based design must be carried out if the system is to achieve its desired performance. An optimal reliability design is one in which all possible means available to a designer have been explored to enhance the reliability of the system with minimum cost under the constraints imposed on the development of a system.

Multiple response optimization for improved machined surface quality

Abstract Work material and cutting and tool parameters have a significant effect on the post-machining condition of a machined component. A case study from industry has been selected where it was observed that work hardening of machined surface leads to distortion of thin sections of the component. A multiple response optimization methodology has been used to identify robust cutting and tool parameter settings to minimize the variation and average value of the surface hardness and to minimize the depth of work hardening of the machined surface. The work material used is CuZn40Al2, which is also the material of the actual component.

A novel approach for production scheduling of a high pressure die casting machine subjected to selective maintenance and a sampling procedure for quality control

Effective maintenance keeps machines in good working condition, improving the machine availability during production. It also minimizes the process failure rate due to component failure, resulting into improved product quality. In this paper the interrelationship between maintenance, production scheduling and quality control is captured using an integrated approach. A mathematical model comprising of total cost of selective maintenance, process quality control using a sampling procedure and production scheduling is developed for a single machine manufacturing system. Simultaneous optimization using the proposed integrated model results into the decision on maintenance actions namely repair, replace and do-nothing for each component, along with the values of parameters for the sampling procedure and the optimal production schedule. A numerical study is presented to demonstrate the applicability of the proposed model. A simulated annealing algorithm is used for obtaining the near optimal solution to the decision parameters. The effectiveness of the proposed approach is compared with the conventional approach of decision making for maintenance, quality control and production scheduling. The results indicate that integrated approach is better as compared to the conventional approach.