Efficient near-optimal procedures for some inventory models with backorders-lost sales mixture and controllable lead time, under continuous or periodic review

This paper considers a number of inventory models with backorders-lost sales mixture, stockout costs, and controllable lead time. The lead time is a linear function of the lot size and includes a constant term that is made of several components. These lot-size-independent components are assumed to be controllable. Both single- and double-echelon inventory systems, under periodic or continuous review, are considered. To authors knowledge, these models have never been previously studied in literature. The purpose of this paper is to analyse and optimize these novel inventory models. The optimization is carried out by means of heuristics that work on an ad hoc approximation of the cost functions. This peculiarity permits to exploit closed-form expressions that make the optimization procedure simpler and more readily applicable in practice than standard approaches. Finally, numerical experiments investigate the efficiency of the proposed heuristics and the sensitivity of the developed models

Optimising replenishment policy in an integrated supply chain with controllable lead time and backorders-lost sales mixture

This paper aims to optimize the inventory replenishment policy in an integrated supply chain consisting of a single supplier and a single buyer. The system under consideration has the features such as backorders-lost sales mixture, controllable lead time, stochastic demand, and stockout costs. The underlying problem has not been studied in the literature. We present a novel approach to formulate the optimization problem, which is able to satisfy the constraint on the number of admissible stockouts per time unit. To solve the optimization problem, we propose two algorithms: an exact algorithm and a heuristic algorithm. These two algorithms are developed based on some analytical properties that we established by analysing the cost function in relation to the decision variables. The heuristic algorithm employs an approximation technique based on an ad-hoc Taylor series expansion. Extensive numerical experiments are provided to demonstrate the effectiveness of the proposed algorithms

An ensemble-learning model for failure rate prediction

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conwip card setting in a flow shop system with a batch production machine

A B S T R A C T This paper presents an analytical technique to determine the optimum number of cards to control material release in a CONWIP system. The work focuses on the card setting problem for a flow-shop system characterised by the presence of a batch processing machine (e.g. a kiln for long heat treatment). To control production, two different static approaches are developed: the first one is used when the bottleneck coincides with the batch processing machine and the second one is proposed when the bottleneck is another machine of the flow shop. In both contexts, by means of the appropriate model, one can optimize the performance of the flow- shop by maximizing the throughput and keeping the work in process at a minimum level. Numerical examples are also included in the paper to confirm the validity of the models and to demonstrate their practical utility

fabrication of fluidic reactors by a customized 3d printing process

Abstract Microfluidic systems demonstrated to improve the analysis of biological and chemical processes by providing a more controlled fluid-handling environment. Typically, microfluidic systems are created in monolithic form by means of microfabrication techniques that constrain designers to work in a two-dimensional space. In this regard, Additive Manufacturing (AM) is a powerful set of technologies that can deal with the complexity of 3D structures producing flow paths with sections differing in size and direction. In this work, the use of a commercial laser-based stereolithography 3D printer has been firstly explored to fabricate transparent channels for flow reactors. A custom 3D printer, based on Digital Light Processing Stereolithography (DLP-SLA), has then been developed with the aim at gaining flexibility and overcoming typical limitations raised from standard commercial solutions. The effectiveness of the developed DLP-SLA 3D printer has been experienced by printing transparent fluidic devices with embedded channels with a specifically designed three-step printing process

Stochastic overall equipment effectiveness

International audienceThis paper focuses on the Overall Equipment Effectiveness (OEE), a key performance indicator typically adopted to support Lean Manufacturing and Total Productive Maintenance. Unfortunately, being a deterministic metric, the OEE only provides a static representation of a process, but fails to capture the real variability of manufacturing performances. To take into account the stochastic nature of the OEE, an approximated procedure based on the application of the Central Limit Theorem is presented: the OEE is considered as a stochastic random variable and its probability density function (pdf) is generated through the aggregation of the pdf of the basic causes of waste. Notwithstanding its approximated nature, the procedure can be applied in most practical cases, since the accuracy is assured provided that the average OEE is lower than 90% and the variability of the losses is high. The validity of the approach has been also confirmed by an industrial application included in the paper. Obtained results demonstrate that the Stochastic OEE can help in battling variation, for it allows to identify the hidden losses that account for most of the variability and to estimate the impacts of potential corrective actions in terms of both efficiency and efficacy

On the solutions in rational expectations models

This paper deals with the solutions to macroeconomic models with rational expectations. A first purpose is to demonstrate that two forms of the efficient-market equation commonly used in the literature may be treated as approximations of the same general equation, of different orders with respect to perturbative forces of the market. Second aim is to show how the perturbative terms can be given explicit forms. Finally, the paper addresses the question of finding contributions which can concur to explain the phenomenon usually referred to as stock price volatility

Optimisation of a simulated-annealing-based heuristic for single row machine layout problem using genetic algorithm

We discuss a procedure to determine the optimal set of parameters relevant to heuristics based on the Simulated Annealing technique, an algorithm which is widely applied to combinatorial problems in the field of manufacturing systems. We consider the search for the best set as a second optimisation problem that we solve by a Genetic Algorithm. The performance of our approach is tested in the particular case of backtracking minimisation in a single row machine layout problem for flexible manufacturing systems

M/M/1 Queuing model with ordinary maintenance and breakdowns

An M/M/1 system with ordinary maintenance and possibility of breakdowns is considered from a practical point of view. An appropriate equation for the probability of n units in the system at any instant of time is written in terms of the Green function of the conventional M/M/1 model and solved by an iterative technique which imposes a periodic regime state. Some Monte Carlo simulations are used to assess the accuracy of the iterative process, i. e. verify that it really converges to the correct solution. Special attention is turned to the analysis of the error that is introduced if the different breakdowns that may occur during the service interval are replaced by a single cumulative waste of time. Numerical results are reported for the special cases in which this cumulative breakdown in placed at the beginning or at the end of the service interval. or is uniformly distributed. To some extent, part of the analysis is deliberately approximated, even if good accuracy is always preserved. The extension to the M/G/1 model is also considered