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

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

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 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

New Challenges for Sustainable Organizations in Light of Agenda 2030 for Sustainability

Sustainability is one of humanity’s most daunting issues at present. Increasing popula- tion, escalation of anthropogenic activities, industrialization, modern agricultural practices that pollute water, air, and soil around the world, and ever-increasing greenhouse gas emissions mean that sustainability is now in doubt [1]. In response to these critical concerns, the world has come up with several initiatives including Agenda 2030. Agenda 2030 is a commitment to eradicate poverty and achieve sustainable development worldwide, ensuring that no one is left behind by 2030. Its adoption was a landmark achievement, providing a shared vision towards sustainable development for all. Its 17 Sustainable Development Goals (SDGs) and 169 targets aim to end the plethora of development problems and deliver a better univers

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\u2019 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 \u201cSmart Hospitals\u201d 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