Coffee capsule impacts and recovery techniques: A literature review

The recently developing coffee market has been characterized by profound changes caused by new solutions and technologies for coffee preparation. The polylaminate materials that compose most popular capsules make them a type of waste that is difficult to manage and recycle. This paper analyses the scientific references that deal with studying and improving the management processes of waste coffee capsules, as well as the studies that have analysed their environmental impact. Through a bibliographic review, some encouraging aspects emerged in the recovery of materials that can be adequately recycled (plastics and metals), as well as their possible use for the production of biogas and energy recovery. The need to manually separate the components that make up the capsule still represents one of the main challenges. Many efforts are still needed to favour the environmental sustainability of this waste from a strategic, technological and consumer empowerment point of view

Spare parts management with Additive Manufacturing (AM): a critical review

Additive Manufacturing (AM) is a promising technology for producing spare parts, due to the wide variety of forms and materials that can be used and their enhanced mechanical properties. Given these features and the low lead times compared to classical manufacturing (CM), AM is now being investigated for the management of spare parts. This literature stream is relatively new, with many works based on different hypotheses (e.g., the reliability of AM parts) and with different conclusions. This critical literature review provides practitioners with information on the models available, their findings, and their limitations. Further research directions are also identified

Spare Parts Replacement Policy Based on Chaotic Models

Poisson point processes are widely used to model the consumption of spare parts. However, when the items have very low consumption rates, the historical sample sizes are too small. This paper presents a modelling technique for spare parts policies in the case of items with a low consumption rate. We propose the use of chaotic models derived from the well-known chaotic processes logistic map and Hénon attractor to assess the behaviour of a set of five medium voltage motors supplying four drives in the rolling mill of a steelmaking plant. Supported by the chaotic models, we conclude that the company needs an additional motor to ensure full protection against shortages

Evaporation Through a Dry Soil Layer: Column Experiments

Modeling of water vapor transport through a dry soil layer (DSL), typically formed in the top soil during dry seasons in arid and semi-arid areas, is still problematic. Previous laboratory experiments in controlled environments showed that the only vapor transport process through the DSL is by Fick's law of diffusion. However, field experiments exhibited consistently higher evaporation rates than predicted by diffusion flow only. Some proposed reasons for the mismatch were: (a) daily cycles of condensation and evaporation in the DSL due to changes in solar radiation; (b) wind effects on air movement in the DSL; (c) atmospheric pressure fluctuations; (d) nonlinear influence of the DSL thickness on the evaporation process. To link the laboratory experiments with field observations, we performed soil column experiments in the laboratory with thick (>50 cm) DSL, and with different wind speeds, two radiative lamp schedules (continuous and 12 h daily cycles) and different thicknesses of DSL. Atmospheric pressure, air temperature and humidity were measured continuously. The results show that the evaporation rates observed are larger than those predicted by diffusion flow only. We found that it was possible to model the evaporation rates as a function of atmospheric pressure fluctuations. In conclusion, atmospheric pressure fluctuations can induce evaporation rates in DSL larger than estimated by diffusion flow only, possibly explaining the discrepancy between laboratory and field evaporation rates

Experimental protocol for the determination of elastic properties at ambient and high pressure by picosecond acoustics technique

This thesis work focused on establishing an experimental protocol for the determination of the materials’ elastic constants at ambient pressure and at high pressure by picosecond acoustics. Picosecond acoustics is a pump-probe experimental technique that allows to measure the travel times of the acoustic waves that propagate across the sample. The acoustic waves’ velocities are derived from the travel times and from the sample thickness. An inversion program developed within the research group allows to extract the elastic constants from the measured sound velocities by inverting the Christoffel equation that relates them to the elastic tensor. The high pressure is generated by the diamond anvil cell (DAC) technology. The investigated samples are magnesium oxide (MgO), a transparent insulator, oriented along the [001] direction, and ruthenium (Ru), an opaque metal, oriented along the [0001] direction. The first was studied at ambient pressure, while the second was studied at both ambient and high pressure. The elastic constants of MgO were extracted with the inversion program and the results obtained agree with the values found in the literature. The values obtained are: C11= (296.96± 0.19) GPa, C44= (153.60 ± 0.10) GPa, C12= (98.78 ± 0.11) Gpa. The elastic constants at ambient pressure of Ru agree with the data in the literature and are: C11= (564± 6) GPa, C33= (626 ± 8) GPa, C44= (182.2 ± 0.5) GPa and C12= (175 ±7) Gpa. The measurements at high pressure on ruthenium did not allow to derive the elastic constants as from the data analysis it emerged that the sample had been damaged during the pressure increase. Probably this was due to the selected pressure transmitting medium of the DAC, that did not guarantee completely the pressure hydrostaticity

Conventional or additive manufacturing for spare parts management: An extensive comparison for Poisson demand

Due to the main peculiarities of spare parts, i.e. intermittent demands, long procurement lead times and high downtime costs when the parts are not available on time, it is often difficult to find the optimal inventory level. Recently, Additive Manufacturing (AM) has emerged as a promising technique to improve spare parts inventory management thanks to a ‘print on demand’ approach. So far, however, the impact of AM on spare parts inventory management has been little considered, and it is not yet clear when the use of AM for spare parts inventory management would provide benefits over Conventional Manufacturing (CM) techniques. With this paper we thus aim to contribute to the field of AM spare parts inventory management by developing decision trees that can be of support to managers and practitioners. To this aim, we considered a Poisson-based inventory management system and we carried out a parametrical analysis considering different part sizes and complexity, backorder costs and part consumption. Moreover, we evaluated scenarios where the order-up-to level is limited to resemble applications with a limited storage capacity. For the first time, the analysis was not limited to just one AM and one CM technique, but several AM and CM techniques were considered, also combined with different post-process treatments, for a total of nine different sourcing alternatives. In addition, the economic and technical performance of the different sourcing options were obtained thanks to an interdisciplinary approach, where experts from production economics and material science were brought together

Indoor Environmental Quality (IEQ): A Comparison between TOPSIS- and PROMETHEE-Based Approaches for Indirect Eliciting of Category Weights

Indoor Environmental Quality (IEQ) has received a great deal of attention in recent years due to the relationship between worker comfort and productivity. Many academics have studied IEQ from both a building design and an IEQ assessment perspective. This latter line of research has mostly used direct eliciting to obtain weights assigned to IEQ categories such as thermal comfort, visual comfort, acoustic comfort, and indoor air quality. We found only one application of indirect eliciting in the literature. Such indirect eliciting operates without the need for imprecise direct weighing and requires only comfort evaluations, which is in line with the Industry 5.0 paradigm of individual, dynamic, and integrated IEQ evaluation. In this paper, we use a case study to compare the only indirect eliciting model already applied to IEQ, based on TOPSIS, to an indirect eliciting method based on PROMETHEE and to a classical direct eliciting method (AHP). The results demonstrate the superiority of indirect eliciting in reconstructing individual preferences related to perceived global comfort

A Fuzzy Logic Control application to the Cement Industry

A case study on continuous process control based on fuzzy logic and supported by expert knowledge is proposed. The aim is to control the coal-grinding operations in a cement manufacturing plant. Fuzzy logic is based on linguistic variables that emulate human judgment and can solve complex modeling problems subject to uncertainty or incomplete information. Fuzzy controllers can handle control problems when an accurate model of the process is unavailable, ill-defined, or subject to excessive parameter variations. The system implementation resulted in productivity gains and energy consumption reductions of 3% and 5% respectively, in line with the literature related to similar applications

DEASort: Assigning items with data envelopment analysis in ABC classes

Multi-criteria inventory classification groups similar items in order to facilitate their management. Data envelopment analysis (DEA) and its many variants have been used extensively for this purpose. However, DEA provides only a ranking and classes are often constructed arbitrarily with percentages. This paper introduces DEASort, a variant of DEA aimed at sorting problems. In order to avoid unrealistic classification, the expertise of decision-makers is incorporated, providing typical examples of items for each class and giving the weights of the criteria with the Analytic Hierarchy Process (AHP). This information bounds the possible weights and is added as a constraint in the model. DEASort is illustrated using a real case study of a company managing warehouses that stock spare parts

Cost-benefit evaluation of investment in natural gas distribution

Investment in the distribution of natural gas must be assessed by combining a technical analysis of the investment and an assessment of the social costs and benefits, to evaluate the impact of the project on social welfare in monetary terms. This paper describes how such an analysis can be conducted, by developing a methodology for the evaluation of investment in the distribution of natural gas. Once the net social benefit (NSB) of the investment has been evaluated, it is also important to assess the degree of reliability of such an estimate. This assessment can be conducted through two types of tests: sensitivity analysis and risk analysis. The critical variables are identified in sensitivity analysis as those that have a significant impact on the predicted outcome when they change. To address any uncertainties in the critical variables, a risk analysis quantifies the probability that the NSB is less than that estimated when using modal values for the critical variables. This type of analysis, combined with a technical evaluation, can be effectively used to assess the social consequences of an investment