Elisa Gebennini

A multiple single-pass heuristic algorithm solving the stochastic assembly line rebalancing problem

Assembly line rebalancing is a problem companies are frequently confronted with as continuous changes in product features and volume demand caused by the volatility of modern markets result in re-definition of assembly tasks and line cycle time fluctuations. Consequently, managers are forced to adjust the balancing of their lines in order to adapt to the new conditions while trying to minimise both increases in completion costs and costs related to changes in task assignment. In particular, when modifications are made to line balancing, costs are incurred for operator training, equipment switching and moving, and quality assurance. The stochastic assembly line rebalancing problem is essentially composed of a multi-objective problem in which two joint objectives, total expected completion cost of the new line and similarity between the new and the existing line, must be optimised. Consequently, this paper presents a multiple single-pass heuristic algorithm developed for the purpose of finding the most complete set of dominant solutions representing the Pareto front of the problem. The operative parameters of the heuristic are set as a result of a great deal of experimentation. Moreover, a multi-objective genetic algorithm is developed and then compared with the proposed heuristic in order to demonstrate its effectiveness. Finally, an illustrative case study is presented.

Optimization models for the dynamic facility location and allocation problem

The design of logistic distribution systems is one of the most critical and strategic issues in industrial facility management. The aim of this study is to develop and apply innovative mixed integer programming optimization models to design and manage dynamic (i.e. multi-period) multi-stage and multi-commodity location allocation problems (LAP). LAP belong to the NP-hard complexity class of decision problems, and the generic occurrence requires simultaneous determination of the number of logistic facilities (e.g. production plants, warehousing systems, distribution centres), their locations, and assignment of customer demand to them. The proposed models use a mixed integer linear programming solver to find solutions in complex industrial applications even when several entities are involved (production plants, distribution centres, customers, etc.). Lastly, the application of the proposed models to a significant case study is presented and discussed.

An innovative container for WEEE collection and transport: details and effects following the adoption.

The content of hazardous components in Waste arising from Electrical and Electronic Equipment (WEEE) is a major concern that urges governments and industry to take measures to ensure proper treatment and disposal. Thus, the European Union issued directives to encourage reuse, recycling and other proper forms of recovery of such waste while companies and academics are still studying methods and technologies for optimizing recovery processes. This paper presents an analysis of the logistics process assuring the correct collection, handling, transportation and storing of WEEE. The experience comes from an Italian WEEE treatment plant (TRED Carpi S.r.l.) where a new kind of container has been introduced in order to improve the logistics system. An evaluation framework is described and used in order to compare different system configurations and assess the advantages emerging from adopting proper equipments for WEEE transport and handling.

An innovative model for WEEE recovery network management in accordance with the EU directives

An increased interest towards environmental respect amongst consumers, managers and researchers is registered, owing both to changing sensitivity and guidelines described in technical regulations. In this scenario, the European Union (EU) directives 2002/96/EC and 2003/108/EC, controlling the management of Wastes of Electric and Electronic Equipments (WEEE) are well-inserted. Companies producing Electric and Electronic Equipments (EEE) become responsible for end of life steps of their products. Hence, great efforts are made to optimise both recovery networks and remanufacturing and recycling processes. This paper proposes an innovative model for recovery network management. Included is a case study.

Discrete time model for two-machine one-buffer transfer lines with restart policy

The paper deals with analytical modeling of transfer lines consisting of two machines decoupled by one finite buffer. In particular, the case in which a control policy (referred as “restart policy”) aiming to reduce the blocking frequency of the first machine is addressed. Such a policy consists of forcing the first machine to remain idle (it cannot process parts) each time the buffer gets full until it empties again. This specific behavior can be found in a number of industrial production systems, especially when some machines are affected by outage costs when stops occur. The two-machine one-buffer line is here modeled as a discrete time Markov process and the two machines are characterized by the same operation time. The analytical solution of the model is obtained and mathematical expressions of the most important performance measures are provided. Some significant remarks about the effect of the proposed restart policy on the behavior of the system are also pointed out.

Modeling waste production into two-machine–one-buffer transfer lines

This article focuses on analytical models of two-machine one-buffer Markov lines including waste production. The aim is to compute the probability of producing good parts, referred to as effective efficiency, when waste production is related to stoppages of the first machine. This problem is common in industrial fields where parts are generated by a continuous process; e.g., in high-speed beverage packaging lines. Two innovative models including waste production are presented: the WP-Basic Model extends the model of a basic two-machine–one-buffer transfer line; the WP-RP Model extends the model of a two-machine–one-buffer transfer line with a restart policy operating on the first machine (i.e., when the first machine is blocked because the buffer is filled, it is not allowed to resume production until the buffer becomes empty). The two existing models are improved by distinguishing, at any time step the first machine is operational, whether it is producing a good or a bad part. The probabilities of the system being in any feasible state are analytically derived for both the WP-Basic Model and the WP-RP Model. Then, the obtained probabilities are used to determine the performance measures of interest; i.e., waste probability and effective efficiency. Finally, some numerical results are provided to illustrate the effectiveness of the WP-Basic Model and the WP-RP Model.

Low cost automation and poka yoke devices: tools for optimising production processes

Low cost automation and poka yoke philosophy assure good results when applied to manufacturing processes with a high incidence of human operators, with a low availability of time for solution implementation and with expensive effects associated with errors in executing operative procedures. Hence, their joint adoption is addressed in order to access the benefits they both guarantee. Specifically, in this paper, the case of a manufacturing line for heat exchangers is studied. Operative tools are redesigned in accordance with both low cost automation and poka yoke philosophy principles. Furthermore, since poka yoke solutions are subdivided between those preventing errors and those detecting them, the former are preferred. It emerges that LCA and poka yoke solutions adopted induce consistent improvements in the line productivity.

The two-machine one-buffer continuous time model with restart policy

This paper deals with the performance evaluation of production lines in which well defined machine start/stop control policies are applied.A modeling approach has been developed in order to reduce the complexity of a two-machine one-buffer line where a specific control policy, called “restart policy”, is adopted. The restart policy exercises control over the start/stop condition of the first machine: when the buffer gets full and, as a consequence, the first machine is forced to stop production (i.e., it is blocked), the control policy keeps the first machine in an idle state until the buffer becomes empty again. The rationale behind this policy is to reduce the blocking frequency of the first machine, i.e. the probability that a blockage occurs on the first machine due to the buffer filling up. Such a control policy is adopted in practice when outage costs (e.g., waste production) are related to each restart of the machine.The two-machine one-buffer line with restart policy (RP line) is here modeled as a continuous time Markov process so as to consider machines having different capacities and working in an asynchronous manner. The mathematical RP model is described along with its analytical solution. Then, the most critical line performance measures are derived and, finally, some numerical examples are reported to show the effects of such a policy on the blocking frequency of the first machine.

A simulation based approach for supporting automated guided vehicles (AGVS) systems design

Automated guided vehicle (AGV) logistic handling system are widely adopted when high transportation capacity and quality of service are the most important characteristics to reach. A large number of mathematical approaches have been developed in years to address AGV systems design and control. Nevertheless, proper performance estimations have to consider the peculiar aspects of the real environment in which the AGV system operates. A simple and effective approach to the stochastic features modelling is the discrete event simulation of the real system. This paper presents a conceptual approach that lead the analyst to set up consistent simulative models to address AGV systems design and performance estimation when applications in end-of-line logistics are considered.

Discrete-time model for two-machine one-buffer transfer lines with buffer bypass and two capacity levels

This article deals with the analytical modeling of transfer lines consisting of two machines decoupled by one finite buffer. The innovative contribution of this work consists in representing a particular behavior that can be found in a number of industrial applications, such as in the ceramics and electronics industries. Specifically, the buffer significantly affects the line’s performance as, when it is accumulating or releasing material (i.e., when one machine is operational and the other machine is under repair), it forces the operational machine to slow down. Conversely, when both machines are operational they can work at a higher capacity since the buffer is bypassed. Thus, two levels for the machine capacity can be identified, based on the conditions of the machines and, consequently, the state of the buffer. The system is modeled as a discrete-time, discrete-state Markov process. The resulting two-Machine one-Buffer Model with Buffer Bypass is here called 2M-1B-BB model. The analytical solution of the model is obtained and mathematical expressions of the most important performance measures are provided. Finally, some numerical results are discussed.