Roberto Montanari

Multi‐attribute classification method for spare parts inventory management

Inventory constraints, costs of lost production, safety and environmental objectives, strategies of maintenance adopted, logistics aspects of spare parts are some of the criteria taken into account, and spare parts classification is thus defined with respect to multiple attributes. In virtue of the large number of the potential operational characteristics to be considered, the decision diagram is integrated with a set of analytic hierarchy process models used to solve the various multi‐attribute decision sub‐problems at the different levels/nodes of the decision tree. An inventory policy matrix is defined to link the different classes of spare parts with the possible inventory management policies so as to identify the “best” control strategy for the spare stocks. The principles of the theory and an actual application in a company operating in the paper industry are reported in the paper.

Supply chain design and cost analysis through simulation

This paper is grounded on a discrete-event simulation model, reproducing a fast moving consumer goods (FMCG) supply chain, and aims at quantitatively assessing the effects of different supply configurations on the resulting total supply chain costs and bullwhip effect. Specifically, 30 supply chain configurations are examined, stemming from the combination of several supply chain design parameters, namely number of echelons (from 3 to 5), re-order and inventory management policies (EOQ vs. EOI), demand information sharing (absence vs. presence of information sharing mechanisms), demand value (absence vs. presence of demand ‘peak’), responsiveness of supply chain players. For each configuration, the total logistics costs and the resulting demand variance amplification are computed. A subsequent statistical analysis is performed on 20 representative supply chain configurations, with the aim to identify significant single and combined effects of the above parameters on the results observed. From effects analysis, bullwhip effect and costs outcomes, 11 key results are derived, which provide useful insights and suggestions to optimise supply chain design.

The classification and regression tree approach to pump failure rate analysis

Abstract In this article, a technique based on rule induction is suggested as non-parametric alternative to determine the expected failure rates of 143 centrifugal pumps included in a oil refinery plant and subjected to different operating conditions. At the same time, the procedure makes it possible to determine the critical operating factors influencing the reliability of the pumps. In particular, the classification and regression tree approach is used to automatically generate rules from an extended data base of the plant concerning information about failures and operating conditions of the different facilities.

The impact of RFID technology on logistics processes of the fashion industry supply chain

This paper aims at quantitatively assessing the impact of radio frequency identification (RFID) technology and electronic product code (EPC) system on the main processes of the fashion industry supply chain. A fashion supply chain, composed of a distribution centre (DC) and a retail store (RS), is examined. A questionnaire survey and several site visits were performed to collect both quantitative and qualitative data related to current (AS IS) supply chain processes of each player investigated. Starting from data collected, re-engineered (TO BE) procedures were designed, hypothesising the implementation of RFID technology. Grounding on the gap between AS IS and TO BE scenarios, a detailed investment evaluation was performed in order to assess the profitability of RFID and EPC implementation in the fashion supply chain, both for each player and for different supply chain configurations. Results show that RFID and EPC implementation is profitable under several scenarios examined, and that the profitability ...

Reverse Logistics: a stochastic EOQ-based inventory control model for mixed manufacturing/remanufacturing systems with return policies

This paper focuses on mixed manufacturing/remanufacturing systems, where manufacturing or purchase of new items integrates product reuse or remanufacturing, with the purpose to achieve a complete and timely demand satisfaction. We formulate a stochastic Economic Order Quantity (EOQ)-based inventory control model for a mixed manufacturing/remanufacturing system. The model is intended to identify the need of placing a manufacturing/purchasing order, to avoid the occurrence of stock-out situations. We then formulate a total cost minimisation problem, to derive the optimal return policy, this latter being a financial incentive paid to customers to increase the flow of returned items. The model developed is investigated through simulations, in order to assess the effect of stochasticity (of demand, return fraction and return delay) on the optimal return policy of the system; then, it is validated through a case study, to derive indications concerning its practical application in real cases. Our study ultimately provides a framework for practitioners to establish EOQ policies in reverse logistics contexts and to evaluate the opportunity of establishing a return policy in those contexts.

Environmental efficiency analysis for enel thermo-power plants

Abstract In this paper, a new method is presented for estimating the environmental efficiency of 15 thermo power plants (TPPs) and their evolution over the years. In particular, the plant environmental efficiency, defined as a function of consumptions, costs and emissions (SO 2 , NO x , ash, and CO 2 ) are considered, taking into account the fuel adopted. The approach is based on a two-step procedure. Firstly, a “Multi Criteria Decision Making” (MCDM) technique is applied to rank the TPPs as a function of the environmental efficiency. In particular the “Technique for Order Preference by Similarity to Ideal Solution” (TOPSIS) is used to order the plants according the six different criteria. Secondary, the TOPSIS ranking analysis is applied with reference to a fuel pollution indicator proposed in the literature, which makes it possible to consider its “environmental quality”. The integration of the pollution indicator with the TOPSIS ranking makes it possible to obtain a graphical output that shows the comparison of the environmental performances between the different plants analysed in an easy and intuitive manner. In addition, concerning the data available for a number of years, it is also possible to study the TPPs environmental efficiency evolution over time.

Criteria for the economic planning of a low power hydroelectric plant

This paper presents an original method for finding the most economically advantageous choice for the installation of micro hydroelectric plants.

Optimisation of storage allocation in order picking operations through a genetic algorithm

This paper explores the use of a genetic algorithm (GA) to optimise item allocation in a warehouse, with the ultimate purpose of reducing the travel time of pickers, thus streamlining order picking operations. The GA is described along with a numerical example, reflecting a fast moving consumer goods warehouse, where items are assumed to be allocated according to a class-based storage system. Starting from that configuration, and taking into account the set of orders to be fulfilled, the GA identifies a new item allocation, which significantly decreases the travel distance (by approximately 20%). This involves a corresponding decrease in the cost of picking operations, and allows the warehouse to respond quicker to the requests of customers. The GA and its numerical implementation are supported by a general purpose software, such as Microsoft Excel®, programmed under visual basic for applications; the resulting tool is thus easy to use in real scenarios.

Failure rate prediction with artificial neural networks

Purpose – To suggest that a multi layer perception based artificial neural network (MLP‐ANN) is a practical instrument to evaluate the expected failure rates of 143 centrifugal pumps used in an oil refinery plant.Design/methodology/approach – A MLP is adopted to weigh up the correlation existing among the failure rates and the several different operating conditions which have some influence in the occurrence.Findings – During the training phase, it is possible to discriminate among those variables closely significant for the final outcome and those which can be kept off from the analysis. In particular, the neural network automatically calculates and classifies the centrifugal pumps in terms of both the failure probability and its variability degree, giving a better analysis instrument to take decisions and to justify them, in order to optimise and fully support an eventual preventive maintenance (PM) program.Originality/value – Aids in decision‐making to reduce the necessity of reactive maintenance activ...

The impact of RFID technology and EPC system on stock-out of promotional items

This paper examines the impact of radio frequency identification (RFID) and EPC Network on out‐of‐stocks of promotional items during a sales promotion in the fast-moving consumer goods (FMCG) context. A mathematical model is developed to estimate savings achievable by reducing the main causes of unavailability of promotional items. In particular, the model compares the current performance of sales promotion of FMCG retail stores, in terms of stock‐out occurrence and related duration, with a re-engineered situation where RFID and EPC are exploited in the store to reduce stock‐out causes. The model has been applied to a retail store of a major Italian distributor of FMCG. Results of the application suggest that RFID and EPC have the potential to substantially reduce economical losses due to unavailability of promotional items, thus proving the economical profitability of their implementation in the FMCG field.