Mauro Gamberi

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.

Multi-objective assembly line balancing considering component picking and ergonomic risk

Display Omitted ALBP distinguishing assembly activities in task execution and component picking.Function to relate component picking time with its features and storage location.MO model to simultaneously minimize assembly line takt time and ergonomic risk.Optimal task assignment to stations and storage location for each component.Industrial case study trade-off configuration: ergonomic risk 36%, takt time +2%. Aim of the assembly line balancing problem (ALBP) is the efficient and effective assignment of assembly tasks to stations in one-piece-flow production systems. Although this problem has been studied for decades, few contributions consider the component picking at assembly station level. Yet, this activity has relevant and practical implications for ALBPs in the industrial context. This paper proposes an innovative multi-objective optimization model for the ALBP to assign the assembly tasks to stations by distinguishing the assembly activities involved in task execution and component picking. Thus, a function is proposed to relate the time required for component picking with the component storage location at assembly station level and the component features, namely dimensions, weight and handiness. The aim of the developed model for the ALBP is the simultaneous minimization of the assembly line takt time and ergonomic risk, both determined by the task execution and component picking activities. Furthermore, the proposed model not only defines the optimal task assignment to stations, but it also determines the optimal storage location of each component between the locations available at the different assembly stations. The multi-objective optimization model is validated with an industrial case study dealing with a kitchen appliance assembly line. The final assembly line balancing configuration proposed is distinguished by remarkable performance for both takt time and ergonomic risk objective functions. Such a balancing leads to 36% ergonomic risk reduction with just 2% takt time increase compared to the correspondent single-objective configurations. These outstanding results are determined by a proper component disposition in the different station storage locations defined by the model.

Design of an Innovative Plant for the Wastewater Recovery and Purification in the Food & Beverage Industry

The food & beverage (F&B) industry is among the most water intensive sectors with thousands of litres per hour of raw water requirement. Starting from the statement of this issue, an overview of the evidences from the field and a quick survey of the existing technologies for the raw water saving through its local collection and treatment before discharge, this paper investigates the design of an innovative industrial plant for the water closed-loop recovery, purification and local reuse. Actually, a prototype of such a plant is working within a mid-size F&B company operating in the Emilia-Romagna region, Italy. The plant nominal capacity is of about 45,000 l/h of discharged wastewater. It integrates water ultra-filtration and reverse osmosis technologies. Details of the functional module design and of the logic of control are in the present paper. Finally, few preliminary evidences from the plant field-test are provided.

ENVIRONMENTAL ASSESSMENT OF AN INNOVATIVE PLANT FOR THE WASTEWATER PURIFICATION IN THE BEVERAGE INDUSTRY

Nowadays, efforts to reduce the resource depletion and environmental emissions from the anthropic activities, are mandatory for sustainable development pattern. Among the key resources to save, pure water is as important as critic due to its scarcity and its essential role for life and growth. Furthermore, during the last decades, rising attention from institutions and industries is toward solutions for the water intensity decrease and wastewater recovery. This paper proposes the environmental assessment of an innovative wastewater collection and purification plant tailored to a mid-size beverage industry aiming at locally closing the loop of the water chain, allowing its recirculation and local reuse. After the description of the functional module features, sizes and design, based on a prototype actually working in Italy, the paper follows the ISO 14040 standards to develop an environmental

CLASS-BASED STORAGE WAREHOUSE DESIGN WITH DIAGONAL CROSS-AISLE

Background: Unit-load (UL) warehouses are among the most diffuse solutions to store items stocked in pallets, while class-based storage (CBS) assignment is an effective strategy balancing the storage space need and the UL traceability. This paper proposes a design strategy to reduce the access time for UL-CBS systems based on the inclusion of one additional diagonal aisle crossing the racks and the parallel aisles accessing the storage bays. Methods: The introduced design strategy is based on the analytic models to compute the access time for one diagonalcross aisle warehouses with 2and 3-CBS system. The minimization of the closed form expressions getting the average time to reach the storage bays allow reducing the travelled paths to store and retrieve (S&R) the ULs. Results: Comparison of the average time to S&R the ULs between traditional warehouses and the proposed configuration highlights the positive impact of the diagonal cross-aisle inclusion. In addition, a case example for a company operating within the food sector shows performance increase of about 33% respect to the correspondent traditional warehouse configuration. Conclusion: The interest in non-traditional warehousing systems raises because of the savings in the time to S&R the ULs. Analytic and even more general models to compute such savings are of help to best design the storage area increasing the inbound handling performances.