Poznań University of Technology

Jędrzejczak P., Collins M.N., Jesionowski T., Klapiszewski Ł.

The construction industry in the 21st century faces numerous global challenges associated with growing concerns for the environment. Therefore, this review focuses on the role of lignin and its derivatives in sustainable construction. Lignin's properties are defined in terms of their structure/property relationships and how structural differences arising from lignin extraction methods influence its application within the construction sector. Lignin and lignin composites allow the partial replacement of petroleum products, making the final materials and the entire construction sector more sustainable. The latest technological developments associated with cement composites, rigid polyurethane foams, paints and coatings, phenolic or epoxy resins, and bitumen replacements are discussed in terms of key engineering parameters. The application of life cycle assessment in construction, which is important from the point of view of estimating the environmental impact of various solutions and materials, is also discussed.

Tirkolaee E.B., Mardani A., Dashtian Z., Soltani M., Weber G.

Recently, large companies have shown a growing tendency to enhance the reliability and sustainability of their supply chains to increase customers’ satisfaction in terms of on-time fulfillment of demands and to be compatible with environmental regulations. Therefore, finding the best approaches to achieve companies’ goals is a crucial concern in supply chain management, and the majority of organizations prefer to cooperate with reliable and sustainable companies. In designing a supply chain, the supplier selection problem, order size identification, and order allocation are midterm decisions that are needed to be made separately. To this end, three levels of the supply chain, i.e., suppliers, central warehouses, and wholesalers are considered. In the first level, to address the sustainable supplier selection problem, a novel hybrid approach based on the fuzzy logic is implemented. This approach applies the Fuzzy Analytic Network Process (FANP) method to ranking criteria and sub-criteria, the fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) is applied to identification of the relationships among the main criteria, and the fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to prioritizing the suppliers. After prioritizing the suppliers, the obtained weights are considered as the input of a tri-objective model designed to optimize the proposed supply chain. The objectives are minimization of the total cost of the chain, maximization of the weighted value of products by taking the account of suppliers’ priorities, and maximization of the reliability of the supply chain. Weighted Goal Programming (WGP) method is then used to deal with multi-objectiveness. To assess the applicability of the suggested methodology, a case study of the lamp supply chain was considered and solved using GAMS/CPLEX solver and optimal policies based on suppliers’ sustainability. The reliability of the supply chain was tested, and sensitivity analyses were also performed on the main parameters of the model.

Tirkolaee E.B., Abbasian P., Weber G.

The performance of waste management system has been recently interrupted and encountered a very serious situation due to the epidemic outbreak of the novel Coronavirus (COVID-19). To this end, the handling of infectious medical waste has been particularly more vital than ever. Therefore, in this study, a novel mixed-integer linear programming (MILP) model is developed to formulate the sustainable multi-trip location-routing problem with time windows (MTLRP-TW) for medical waste management in the COVID-19 pandemic. The objectives are to concurrently minimize the total traveling time, total violation from time windows/service priorities and total infection/environmental risk imposed on the population around disposal sites. Here, the time windows play a key role to define the priority of services for hospitals with a different range of risks. To deal with the uncertainty, a fuzzy chance-constrained programming approach is applied to the proposed model. A real case study is investigated in Sari city of Iran to test the performance and applicability of the proposed model. Accordingly, the optimal planning of vehicles is determined to be implemented by the municipality, which takes 19.733 h to complete the processes of collection, transportation and disposal. Finally, several sensitivity analyses are performed to examine the behavior of the objective functions against the changes of controllable parameters and evaluate optimal policies and suggest useful managerial insights under different conditions. • Addressing the sustainability of location-routing problem under the pandemic situation • Applying fuzzy chance-constrained programming technique to address the uncertainty • Implementing weighted goal programming method to deal with the mutli-objectiveness • Investigating applicability of the proposed methodology using a real case study.

Marques F., Balcerzak M., Winkelmann F., Zepon G., Felderhoff M.

High-entropy alloys (HEAs) are a new class of alloys that has been investigated for hydrogen storage. Here we discuss the design, synthesis, and hydrogen storage properties of HEAs studied to date.

Ławniczak Ł., Woźniak-Karczewska M., Loibner A.P., Heipieper H.J., Chrzanowski Ł.

Crude oil-derived hydrocarbons constitute the largest group of environmental pollutants worldwide. The number of reports concerning their toxicity and emphasizing the ultimate need to remove them from marine and soil environments confirms the unceasing interest of scientists in this field. Among the various techniques used for clean-up actions, bioremediation seems to be the most acceptable and economically justified. Analysis of recent reports regarding unsuccessful bioremediation attempts indicates that there is a need to highlight the fundamental aspects of hydrocarbon microbiology in a clear and concise manner. Therefore, in this review, we would like to elucidate some crucial, but often overlooked, factors. First, the formation of crude oil and abundance of naturally occurring hydrocarbons is presented and compared with bacterial ability to not only survive but also to utilize such compounds as an attractive energy source. Then, the significance of nutrient limitation on biomass growth is underlined on the example of a specially designed experiment and discussed in context of bioremediation efficiency. Next, the formation of aerobic and anaerobic conditions, as well as the role of surfactants for maintaining appropriate C:N:P ratio during initial stages of biodegradation is explained. Finally, a summary of recent scientific reports focused on the removal of hydrocarbon contaminants using bioaugmentation, biostimulation and introduction of surfactants, as well as biosurfactants, is presented. This review was designed to be a comprehensive source of knowledge regarding the unique aspects of hydrocarbon microbiology that may be useful for planning future biodegradation experiments. In addition, it is a starting point for wider debate regarding the limitations and possible improvements of currently employed bioremediation strategies.

Cinelli M., Kadziński M., Gonzalez M., Słowiński R.

Decision making is a complex task that involves a multitude of perspectives, constraints, and variables. Multiple Criteria Decision Analysis (MCDA) is a process that has been used for several decades to support decision making. It includes a series of steps that systematically help Decision Maker(s) (DM(s)) and stakeholders in structuring a decision making problem, identifying their preferences, and building a decision recommendation consistent with those preferences. Over the last decades, many studies have demonstrated the conduct of the MCDA process and how to select an MCDA method. Until now, there has not been a review of these studies, nor a proposal of a unified and comprehensive high-level representation of the MCDA process characteristics (i.e., features), which is the goal of this paper. We introduce a review of the research that defines how to conduct the MCDA process, compares MCDA methods, and presents Decision Support Systems (DSSs) to recommend a relevant MCDA method or a subset of methods. We then synthesize this research into a taxonomy of characteristics of the MCDA process, grouped into three main phases, (i) problem formulation, (ii) construction of the decision recommendation, and (iii) qualitative features and technical support. Each of these phases includes a subset of the 10 characteristics that helps the analyst implementing the MCDA process, while also being aware of the implication of these choices at each step. By showing how decision making can be split into manageable and justifiable steps, we reduce the risk of overwhelming the analyst, as well as the DMs/stakeholders during the MCDA process. A questioning strategy is also proposed to demonstrate how to apply the taxonomy to map MCDA methods and select the most relevant one(s) using real case studies. Additionally, we show how the DSSs for MCDA method recommendation can be grouped into three main clusters. This proposal can enhance a traceable and categorizable development of such systems.

Pimenov D.Y., Bustillo A., Wojciechowski S., Sharma V.S., Gupta M.K., Kuntoğlu M.

The wear of cutting tools, cutting force determination, surface roughness variations and other machining responses are of keen interest to latest researchers. The variations of these machining responses results in change in dimensional accuracy and productivity upto great extent. In addition, an excessive increase in wear leads to catastrophic consequences, exceeding the tool breakage. Therefore, this article discusses the online trend of modern approaches in tool condition monitoring while different machining operations. For this purpose, the effective use of new sensors and artificial intelligence (AI) is considered and followed during this holistic review work. The sensor systems used for monitoring tool wear are dynamometers, accelerometers, acoustic emission sensors, current and power sensors, image sensors, other sensors. These systems allow to solve the problem of automation and modeling of technological parameters of the main types of cutting, such as turning, milling, drilling and grinding. The modern artificial intelligence methods are considered, such as: Neural networks, Image recognition, Fuzzy logic, Adaptive neuro-fuzzy inference systems, Bayesian Networks, Support vector machine, Ensembles, Decision and regression trees, k-nearest neighbors, Artificial Neural Network, Markov model, Singular Spectrum Analysis, Genetic algorithms. Discussions also includes the main advantages, disadvantages and prospects of using various AI methods for tool wear monitoring. Moreover, the problems and future directions of the main processing methods using AI models are also highlighted.

Pimenov D.Y., Mia M., Gupta M.K., Machado A.R., Tomaz Í.V., Sarikaya M., Wojciechowski S., Mikolajczyk T., Kapłonek W.

Products made of titanium and its alloys are widely used in modern areas like the mechanical engineering, instrument making, aerospace and medical sector. High strength and low thermal conductivity are the causes of difficulties with the machinability of these alloys. It is important to find ways to increase machinability by cutting titanium alloys. One way to implement this is to apply various methods of cooling on workpieces of titanium alloys and on cutting tools during machining. In this review article, an extensive analysis of the literature on such cooling techniques as dry, conventional cooling system, minimum quantity of lubricant (MQL), minimum quantity cooling lubrication (MQCL), cryogenic lubrication, and high-pressure cooling (HPC) is performed. The following groups of Ti alloys are considered: high-strength structural and high-temperature Ti alloys, intermetallic compounds, pure titanium, as well as composites CFRPs/Ti alloys. For the processes of turning, milling, drilling, and grinding, etc. it is shown how the type of cooling affects the surface integrity include surface roughness, tool wear, tool life, temperature, cutting forces, environmental aspects, etc. The main advantages, disadvantages and prospects of different cooling methods are also shown. The problems and future trends of these methods for the machining of Ti and its alloys are indicated.

Wojciechowski S., Matuszak M., Powałka B., Madajewski M., Maruda R.W., Królczyk G.M.

This study focuses on the prediction of cutting forces during micro end milling using a novel approach that takes into account the chip thickness accumulation phenomenon. The proposed original force model considers the micro end milling kinematics, geometric errors of the machine tool–toolholder–mill system, elastic and plastic deformations of workpiece correlated with the minimum uncut chip thickness, and flexibility of the slender micro end mill. It also includes a novel analytical approach for the instantaneous area of cut. The chip thickness accumulation phenomenon can be manifested as chip thickness variations in the current tool rotation, resulting from material burnishing and elastic recovery in all previous tool rotations. The predicted forces consider the minimum uncut chip thickness value, which has been estimated directly from the micromilling process of AISI 1045 steel based on an original analytic–experimental approach that applies the identification of a stagnant point in the milling process. The results obtained show that the instantaneous and average micromilling forces determined using the proposed model have considerably better conformity with the experimental forces than those predicted using the commonly used rigid micro end milling model. Moreover, the non-linearity of the cutting forces as a function of feed per tooth is strongly affected by multiple cutting mechanism transitions observed during micromilling with uncut chip thicknesses close to the minimum uncut chip thickness value.

Tirkolaee E.B., Mahdavi I., Esfahani M.M., Weber G.

The excessive expansion of cities and the consequent increase in urban population, especially in recent years, have led to a significant increase in consumptions and generations of different types of municipal solid waste (MSW). In this research, a robust green location-allocation-inventory problem (LAIP) is investigated to design an efficient MSW management system. Since the exact amount of MSW composition in different regions is not known and is uncertain, robust optimization technique is applied to formulate the problem as a mixed-integer linear programming (MILP) model. The objective is to minimize the total cost including fixed locational costs of collection and processing/disposal facilities, operational costs of facilities, transportation costs, penalty costs of non-collected waste and costs arising from pollution emissions. The validation of the proposed model is performed by different problems based on real-life data in deterministic and uncertain conditions using CPLEX solver of GAMS software. Then, the effects of greenness are evaluated by performing a sensitivity analysis on the parameter of pollution cost. Finally, the concept of robustness worthiness threshold (RWT) under budget constraint is introduced and discussed.