Purpose -The purpose of this paper is to attempt to get more in-depth understanding of real life processes, for which theoretical models are not available and knowledge about the processes is empirical. The processes are noisy; interaction effects may or may not be present. The paper attempts to formulate a more practical view, related to such processes. This is sought to obtain improved ways of experimentation for process and product optimization. Design/methodology/approach -Functional forms are discussed when there would be no interactions. A conceptual process is considered to highlight some important aspects of interactions. A discrete search method of optimizing a process or a product is suggested. Analysis is done for the method and a numerical experiment is carried out to investigate the performance of the method. This is further verified with a real life case study. Findings -Some conditions are obtained when the search method would yield an optimal solution. The numerical experiment and the case study indicate satisfactory performance of the method. A set of preferable steps, utilizing the method, is suggested to conduct experiments.Research limitations/implications -The paper suggests a set of steps to carry out experiments in order to optimize a process, and give the rationale why these would work for some processes. The steps are not so general to include all kinds of processes which may occur. Practical implications -Improved ways of experimentation would help to arrive at optimal values of parameters in products and processes, with less cost and time. Originality/value -The paper suggests a new discrete search method of optimization and a particular approach, based on the method, to the conduct of experiments.
Purpose
– The purpose of this paper is to propose a few steps to enhance maintenance effectiveness in practice.
Design/methodology/approach
– The author reviews the strengths and limitations of different approaches to maintenance management (MM). Some relevant practical observations of reliability engineering are discussed. Based on these, and drawing on the research on MM in relevant literature, the author suggests a few steps, suitable for implementation, for effective MM.
Findings
– Review of available approaches to MM and some factors of reliability engineering points to some ways to improve maintenance effectiveness in the practical sense.
Practical implications
– Implementation of the steps, as suggested in the paper, should enhance the effectiveness of MM leading to higher machine uptimes with less of maintenance costs. In such steps, the ease of implementation in practical situations has been given due importance.
Originality/value
– In the steps, called as an “Actionable Program for Maintenance,” that the author suggests, he has highlighted some issues, and has made some suggestions, which are new.
In this article a single-item, continuous monitoring (s, Q) inventory model with probabilistic demand following Bernoulli distribution and probabilistic lead time of order replenishment is considered. The model extends a Bernoulli demand inventory model, available in the literature. We allow a non-zero reordering inventory position. Some properties are shown for the model and a search method is given to find the optimal values of the policy parameters. A numerical experiment is done for the model and some observations are made.
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