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

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

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

New Project Financing and Eco-Efficiency Models for Investment Sustainability

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

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

A building block for the decomposition analysis of production lines with restart policy

The paper presents a method for the performance evaluation of long lines with machines controlled by a restart policy. The restart policy, typical of packaging lines in the food and beverage industry, aims to reduce the occurrence of blocking events on critical machines: when any critical machine gets blocked sinceits downstream buffer is full, it is prevented from resuming production until the buffer is once again empty.First, an analytical model for a building block with restart policy and multiple failure modes is developed and its solution derived. Then, the paper shows how the new model can be included in a decomposition technique based on a multiple failure approach. Some validation results are also provided for three-machine two-buffer lines with a restart policy on the first machine

Joint design of LGV and pallet shuttle fleets for warehouse automation

This paper deals with emerging automation technologies for pallet handling in multi pallet-deep rack storage systems. In particular, this study investigates opportunities resulting from the adoption of pallet shuttles (PSs) for material handling within the rack structure, i.e. for put-away and retrieval operations from the rack face to the specific pallet location and viceversa. PSs may be used in combination with both manually-driven forklift trucks and Laser Guided Vehicles (LGVs) providing material transport from the end-of-line area to the rack storage and from the rack storage to the loading area. The focus of this study is on the combined use of PSs and LGVs so as to discuss the design of a fully automated warehouse. PSs help to overcome the disadvantages related to one of the most commonly used and space efficient type of racks storage, i.e. drive-in racks or similar solutions. Pallets stored in drive-in racks are not independently accessible so that all the levels of a certain lane must be devoted to the same item type and the amount of time to access the pallet locations increases as the lane depth and the number of levels increase. This may lead to efficiency losses. On the contrary, PSs allow different item types to be stored in independent levels of the same lane, so that an higher storage efficiency can be obtained even in long racks. It should be pointed out that methods to support the design of a full automated logistics system are still in an early stage of development. In particular, to the authors' knowledge, studies about the joint design of LGV and PS fleets are not proposed in literature. Thus, this study aims to develop an analytical model for the integrated dimensioning of the fleet of PSs and the fleet of LGVs in a storage system. Given a fleet of PSs acting as the server of the system, the proposed model provides the pallet shuttle utilization rate as a function of the number of LGVs, by taking into consideration the storage area layout and the production and delivery flows. The model identifies sets of feasible solutions, expressed in terms of number of LGVs and PSs, with the same PS utilization rate, i.e. that can be represented by iso-utilization contour lines. Finally, through the application of queuing theory results, the PS utilization rate of a certain set of solutions can be related to the expected cycle time (order release to shipment). The validity of the model is proved by discussing a real case study

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, 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