New project financing and eco-efficiency models for investment sustainability

In the paper, we introduce the Special Issue entitled “New Project Financing and EcoEfficiency Models for Investment Sustainability”, and later present the form and contents of the thematic issue

A novel throughput control algorithm for semi-heterarchical industry 4.0 architecture

Modern market scenarios are imposing a radical change in the production concept, driving companies’ attention to customer satisfaction through increased product customization and quick response strategies to maintain competitiveness. At the same time, the growing development of Industry 4.0 technologies made possible the creation of new manufacturing paradigms in which an increased level of autonomy is one of the key concepts to consider. Taking the advantage from the recent development around the semi-heterarchical architecture, this work proposes a first model for the throughput control of a production system managed by such an architecture. A cascade control algorithm is proposed considering work-in-progress (WIP) as the primary control lever for achieving a specific throughput target. It is composed of an optimal control law based on an analytical model of the considered production system, and of a secondary proportional-integral-derivative controller capable of performing an additional control action that addresses the error raised by the theoretical model’s. The proposed throughput control algorithm has been tested in different simulated scenarios, and the results showed that the combination of the control actions made it possible to have continuous adjustment of the WIP of the controlled production system, maintaining it at the minimum value required to achieve the requested throughput with nearly zero errors

Can public-private partnerships foster investment sustainability in smart hospitals?

This article addresses the relationship between Public-Private Partnerships (PPP) and the sustainability of public spending in smart hospitals. Smart (technological) hospitals represent long-termed investments where public and private players interact with banking institutions and eventually patients, to satisfy a core welfare need. Characteristics of smart hospitals are critically examined, together with private actors' involvement and flexible forms of remuneration. Technology-driven smart hospitals are so complicated that they may require sophisticated PPP. Public players lack innovative skills, whereas private actors seek additional compensation for their non-routine efforts and higher risk. PPP represents a feasible framework, especially if linked to Project Financing (PF) investment patterns. Whereas the social impact of healthcare investments seems evident, their financial coverage raises growing concern in a capital rationing context where shrinking public resources must cope with the growing needs of chronic elder patients. Results-Based Financing (RBF) is a pay-by-result methodology that softens traditional PPP criticalities as availability payment sustainability or risk transfer compensation. Waste of public money can consequently be reduced, and private bankability improved. In this study, we examine why and how advanced Information Technology (IT) solutions implemented in "Smart Hospitals" should produce a positive social impact by increasing at the same time health sustainability and quality of care. Patient-centered smart hospitals realized through PPP schemes, reshape traditional healthcare supply chains with savings and efficiency gains that improve timeliness and execution of care

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

Abstract 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

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 centers), 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 centers, customers, etc.). Lastly, an application of the proposed models to a significant case study is presented and discussed

Reti distributive multilivello. Ottimizzare pi\uf9 che si pu\uf2

Oggi molte aziende si trovano di fronte al problema cruciale di decidere simultaneamente dove ubicare nuovi impianti produttivi e distributivi e come servire i propri clienti. Il presente studio propone una famiglia di modelli di programmazione lineare di tipo cost-based capaci di supportare l\u2019ottimizzazione di una rete logistica operante nel mercato mondiale. I modelli proposti sono stati applicati offrendo notevoli risparmi di costo nella logistica in Arcotronics S.p.A, azienda bolognese leader nella produzione di componenti elettronici e di macchine automatiche

AN INTEGRATED PRODUCTION-DISTRIBUTION MODEL FOR THE DYNAMIC LOCATION AND ALLOCATION PROBLEM WITH SAFETY STOCK OPTIMIZATION

The design and management of a multi-stage production-distribution system is one of the most critical problems in logistics and in facility management. Companies need to be able to evaluate and design different configurations for their logistic networks as quickly as possible. This means coordinating the entire supply chain effectively in order to minimize costs and simultaneously optimize facilities location, the allocation of customer demand to production/distribution centers, the inbound and outbound transportation activities, the product flows between production and/or warehousing facilities, and the reverse logistics activities, etc. Full optimization of supply chain is achieved by integrating strategic, tactical, and operational decision making in terms of the design, management, and control of activities. The cost-based and mixed-integer programming model presented in this study has been developed to support management in making the following decisions: the number of facilities (e.g. warehousing systems, distribution centers), the choice of their locations and the assignment of customer demand to them, and also incorporate tactical decisions regarding inventory control, production rates, and service level determination in a stochastic environment. This paper presents an original model for the dynamic location allocation problem with control of customer service level and safety stock optimization. An experimental analysis identifies the most critical factors affecting the logistics cost, and to finish, an industrial application is illustrated demonstrating the effectiveness of the proposed optimization approach

A methodology for estimating the operating costs of production lines

The paper proposes a methodology for the cost assessment of production lines with unreliable machines and finite buffers. This methodology is based on the new concept of "Line Equipment Cost" (LEC), that is the actual operating cost of a certain machine which is used into a certain line configuration. For each machine, this kind of cost not only depends on a set of static parameters describing the statistical and structural properties of the machine, but also on its actual performance which, in turn, strictly depends on the specific line configuration where the machine is installed. If the line configuration is modified (e.g., more/less buffer space is available) the machine's performance is expected to improve/degrade so that its LEC value, which dynamically expresses the machine's actual operating cost, must be properly adjusted. Hence, in order to evaluate any production line, first the specific LEC values of the single machines in that line should be computed, then the "Total Line Cost" (TLC) can be determined by summing up those LEC values. Finally, the paper provides some numerical results in order to show the applicability of the proposed methodology which can be used not only to evaluate the actual operating cost of a specific production line (expressed by the TLC value), but also to compare different line configurations in order to drive strategic decision

A methodology for estimating the operating costs of production lines

The paper proposes a methodology for the cost assessment of production lines with unreliable machines and finite buffers. This methodology is based on the new concept of "Line Equipment Cost" (LEC), that is the actual operating cost of a certain machine which is used into a certain line configuration. For each machine, this kind of cost not only depends on a set of static parameters describing the statistical and structural properties of the machine, but also on its actual performance which, in turn, strictly depends on the specific line configuration where the machine is installed. If the line configuration is modified (e.g., more/less buffer space is available) the machine's performance is expected to improve/degrade so that its LEC value, which dynamically expresses the machine's actual operating cost, must be properly adjusted. Hence, in order to evaluate any production line, first the specific LEC values of the single machines in that line should be computed, then the "Total Line Cost" (TLC) can be determined by summing up those LEC values. Finally, the paper provides some numerical results in order to show the applicability of the proposed methodology which can be used not only to evaluate the actual operating cost of a specific production line (expressed by the TLC value), but also to compare different line configurations in order to drive strategic decision