Marco Bortolini

Multi-objective design of multi-modal fresh food distribution networks

This paper presents a methodology to jointly minimise the operating cost, the carbon footprint and the delivery time in the design of multi-modal fresh food distribution networks. A tri-objective linear programming model optimises such criteria overcoming the widely adopted methodologies focused on the network cost minimisation, only. A practical selection rule supports the final network structure definition, leading to an effective trade-off among the three objective functions. The market demand supply, the producer capacity limits and the food quality decrease during shipment, i.e., perishability, limit the feasibility region. The paper applies the proposed model to an industrial case study dealing with the distribution of fruits and vegetables from a set of Italian producers to multiple European retailers through a multi-modal (truck, train and air) distribution network. The case study key results suggest the possibility to reduce the CO2 emissions without relevant cost increase.

A learning model for the allocation of training hours in a multistage setting

In line with the continuous improvement theory, the learning phenomenon is often incorporated into models for predicting the evolution of the unitary quality costs. In this paper, the quality metric predicted is the rate of supplied non-conforming units through a learning process with autonomous and induced sources of experience. The former is simply learning by doing, i.e. supplying, whilst the latter is driven by the allocation of training hours to suppliers. A revised learning model with time-varying learning rates is proposed for embracing both these effects into a multistage assembly/production setting. A single-period prevention–appraisal–failure cost function is achieved, and the sample inspection rates adopted among suppliers are also considered in order to evaluate their effect. If these sample rates are given, the goal of allocating the training hours among suppliers is pursued by means of integer linear programming. Otherwise, a mixed-integer quadratic problem arises for the concurrent allocation of training hours and inspection sample rates among suppliers. A case study is finally carried out for demonstrating the applicability of the model, as well as for providing managerial insights.

Hierarchical approach for paced mixed-model assembly line balancing and sequencing with jolly operators

In order to increase flexibility and reduce costs, several companies adopt mixed-model assembly lines whose output products are variations of the same basic model with specific and distinctive attributes. Unfortunately, such attributes typically lead to variations in the task process times. In the case of un-paced buffered assembly lines, these variations are smoothed by buffers with consequences in terms of work-in-progress, costs, space utilisation and lower productivity control. To face such weaknesses, some companies adopt paced un-buffered assembly lines where the cycle time is controlled by the continuous/synchronous moving of the products from the first to the last assembly station. In such contexts, the possibility of assembling different models with different assembly times can be managed through the use of supplementary flexible workforce. This article introduces an innovative balancing and sequencing hierarchical approach for paced mixed-model assembly lines using supplementary flexible workforce called ‘jolly operators’. The goals are to minimise the number of jolly operators and to limit the occurrence of work-overloads, which typically result in out-of-the-line assembly completion. The proposed approach is preliminary validated and applied to a case study from an Italian company assembling industrial air-dryers.

Stochastic timed Petri nets to dynamically design and simulate industrial production processes

Stochastic timed Petri nets are among the most effective languages to model event driven uncertain processes. Their adoption in the industrial sector is even more diffuse and of potential help for the practitioners. This paper presents a stepwise approach to support the dynamic design and simulation of manufacturing and assembly production processes. An industrial application from the white good sector, based on a semi-automatic assembly line is, further, discussed demonstrating the approach flexibility and the modelling language key strengths. The stochastic timed Petri net model for such a scenario is described together with the simulation outcomes of interest for the assembly line design and the production and maintenance activity scheduling.