Equipment Selection Problem Research Articles

Application of the R method in solving material handling equipment selection problems

In manufacturing industries, material handling equipment plays a vital role and is considered as one of the important pillars to increase production efficiency. Hence, the selection of appropriate material handling equipment for a specific task is well acknowledged, but the complexity of this selection process drastically increases with the rise in the number of alternative equipment available in the market and a set of conflicting evaluation criteria. To resolve this problem, several multi-criteria decision-making (MCDM) techniques have been proposed by past researchers. In this paper, the application potentiality of a newly developed MCDM technique, i.e. R method is explored while solving five material handling equipment selection problems, i.e. conveyor, automated guided vehicle (AGV), stacker, wheel loader and excavator. The derived ranking results are contrasted with other popular MCDM techniques to validate its potentiality in shortlisting the candidate alternatives from the best to the worst, which would ultimately help in improving the overall efficiency of the manufacturing processes.

Research on Selection and Matching of Truck-Shovel in Oversized Open-Pit Mines

The equipment investment is large and the annual operating cost is high in oversized open-pit mines. The rationality of the truck-shovel selection and matching has a more prominent influence on the economic benefit of mines. Therefore, we set up an optimization method of truck-shovel selection for oversized open-pit mines, and developed a software system of truck-shovel matching to solve the problem of truck-shovel selection and matching for oversized open-pit mines. First, based on the likelihood statistics method to decide the reasonable quantity range of shovels in the oversized open-pit mine, the selection and matching of shovels under different production scales are realized according to the production ability equation of shovels. Then, according to the principal of deciding the truck by shovel, and by deciding the shovel equipment, the truck-shovel efficiency model is constructed, the proper bucket-to-capacity ratio is obtained in the oversized open-pit mine, and the economic range of truck matching under different shovel specifications is determined by the bucket-to-ability ratio. Finally, using this method, the software system of truck-shovel matching is developed by using C# language, which can automatically calculate the quantity of equipment and the material consumption. The results show that the reasonable number of shovels for the oversized open-pit mine should be 4~7, and the bucket-to-capacity ratio should be 4~5:1. When the annual excavation quantity of the mine is 80~150 million tons, the 35~55 m3 shovels should be the mainstream specification. The research results were applied to a new oversized open-pit mine in Tibet, China, and the problem of equipment selection was solved.

Multi-objective collaborative assembly line design problem with the optimisation of ergonomics and economics

Manufacturing systems are socio-technical systems, with explicit interactions between humans and technologies in shared workspaces. These shared workspaces could also be called hybrid collaborative manufacturing systems, which involve workers as well as technological equipment and combine the benefits of human workers and new Industry 4.0 technologies, such systems are particularly useful in a context requiring flexibility and adaptability. Furthermore, the new Industry 5.0 approach has the objective to shift toward more human-centric and resilient manufacturing systems. The key problems to solve in the design of collaborative manufacturing systems are the combinatorial assembly line balancing problem and the equipment selection problem. An efficient and sustainable line requires a cost-effective choice of equipment while improving the ergonomics and the safety of workers. Both decisions of balancing workload and the assignment of equipment impact the ergonomics of a collaborative system and present conflicting criteria. To this end, we propose a multi-objective approach, the objectives are the optimisation of the investment costs and the ergonomics with a fatigue and recovery criterion. We propose to linearise the fatigue and recovery to formulate a new Mixed Integer Linear Programming formulation. We developed an exact multi-objective solving algorithm based on the ϵ-constraint to obtain the trade-off between these objectives. We conducted numerical experiments with different instances from the literature with promising results for instances with up to 45 operations. Finally, we discuss insightful managerial conclusions and future research perspectives.

ESPDS

In this paper, we introduce a Microsoft Excel Workbook containing the software Equipment Selection Problem DS (ESPDS) that recognizes the special structure of the equipment selection problem. The ESPDS approach is based on the context of the Brazilian forestry sector using detailed equipment maintenance schedules. No special restrictions are needed on cost inputs over time or technologies. The output is an equipment schedule that can be used to project equipment investment needs, operational costs, and tree harvesting costs. ESPDS can be applied to support companies and contractors in order to choose the best option for their operations, as well as to achieve better equipment purchase agreements. We will show how ESPDS will also be useful in providing longer term estimates of production costs. The sensitivity analysis shows how different inputs and maintenance polices can affect the best alternative. A numerical example is included considering the entrance of a specific technology that increases the equipment productivity in order to examine whether it can change the solution. ESPDS is intuitive, flexible, and easy to calculate. Although designed for the forestry industry, the approach is readily transferable to other sectors. ESPDS may be found on the web at the following URL: <a target="_blank" rel="nofollow" href="https://www.researchgate.net/publication/350811380_ESPDS_workbook">https://www.researchgate.net/publication/350811380_ESPDS_workbook</a>.

Solving Material Handling Equipment Selection Problems in an Industry with the Help of Entropy Integrated COPRAS and ARAS MCDM techniques

Solving Material Handling Equipment Selection Problems in an Industry with the Help of Entropy Integrated COPRAS and ARAS MCDM techniques

APPLICATION OF FUZZY ELECTRE METHOD WITH TRAPEZOIDAL FUZZY NUMBERS

The article is devoted to the problem of multi-criteria decision-making. Methods for solving this problem can be divided into two large groups:methods using the aggregation of all alternatives according to all criteria and the solution of the resulting single-criterion problem. The second group isassociated with the procedure of pairwise comparisons and stepwise aggregation. The first group includes methods: weighted average sum,product and their various modifications, the second group includes - AHP, ELECTRE, TOPSIS, PROMETHEE, ELECTRE. For many problemsassessment of the criteria implemented by experts and presented in linguistic form. The effective approach for dealing with linguistic information is fuzzyset theory proposed by L. Zadeh. In this paper is proposed fuzzy ELECTRE method. This method is presented in details. As application problem is usedthe equipment selection problem The issues of practical implementation of this method are discussed in details. The results of the solution test problem at all stages are presented.

Construction Equipment Selection through Scenario-Based FDEA: Truck-Mixer Drums

This study aims to select the most suitable truck-mixer drum (TMD) for construction firms and to present a scenario-based approach to the construction equipment selection problem through the fuzzy data envelopment analysis (FDEA). The technical data of TMDs for quantitative criteria were initially obtained from three TMD companies operating in Turkey. A semi-structured questionnaire survey was then applied to 90 users (i.e., ready-mixed concrete companies) of these TMD brands for qualitative criteria. A scenario analysis, including four different scenarios, was lastly carried out by using FDEA. Considering each scenario, the best alternative was identified for TMD buyers. This study may be beneficial for researchers who can investigate (i) the decision-making process in the domain of the construction equipment selection and (ii) selection criteria of TMDs. This study may also help both potential buyers to make proper equipment selection decisions and TMD manufacturers to improve their products and competitiveness. In terms of originality, the study is first to focus on the selection process and criteria of TMDs. Similarly, FDEA was utilized for the first time in a construction equipment selection problem. As a limitation, the number of respondents, criteria, and alternatives might be increased to reveal more robust solutions.

APPLICATION OF TOPSIS METHOD WITH TRAPEZOIDAL FUZZY NUMBERS

The article is devoted to the problem of multi-criteria decision making. As application problem is used the equipment selection problem. The analysis of existing methods for solving this problem is given. As a method for solving this problem fuzzy TOPSIS (The Technique for Order of Preference by Similarity to Ideal Solution) is proposed. This method is based on ideal solution approach. The issues of practical implementation of this method are discussed in details. The results of the solution test problem at all stages are presented.

Application of the Stacking and LACP Technology in Communications Networks

A key factor that has been winning market competitive advantage by carrier markets is how to solve the selection of equipments with lowest cost which provides a reasonable solution on network security and topology. By introducing the stacking technology, this paper gives a detailed explanation on how to use the lowest cost to solve the equipment selection problem and the devices’ hot backup. As the same time, it is shown that the network link aggregation hot backup is resolved by using the Link Aggregation Control Protocol (LACP). Once there is a failure in both a link and an equipment, the system would detect the failure and automatically switch to the backup link and equipment to ensure the network security.

An integrated group FWA-ELECTRE III approach based on interval type-2 fuzzy sets for solving the MCDM problems using limit distance mean

The material handling equipment (MHE) has a close connection with layout of machinery and plays the important role in productivity of servicing or manufacturing systems. Since each of MHE has distinct characteristics than the others with respect to conflicting criteria and design experts may state the different subjective judgments with respect to qualitative criteria, the material handling equipment selection problem (MHESP) can be taken into account as a group multi-criteria decision-making (GMCDM) problem. In this paper, a version of type-2 fuzzy sets (T2FSs), named Gaussian interval type-2 fuzzy sets (GIT2FSs), is first used as an alternative to the traditional triangular membership functions (MFs) to weight criteria and sub-criteria and also evaluate of alternatives with respect to sub-criteria. The synthetic value method of GIT2FSs is then carried out to convert the assessments stated as GIT2FSs for each alternative with respect to each sub-criterion and also weights of criteria (sub-criteria) into the single fuzzy rating and weight, respectively. Then, the fuzzy weighted average (FWA) approach is adopted to integrate the single fuzzy ratings of each alternative with respect to sub-criteria and the single fuzzy weights of sub-criteria under each criterion with the aggregated weighted ratings. In next stage, ELECTRE III (ELimination Et Choix Traduisant la Realite´—elimination and choice translation reality) is generalized with GIT2FSs to select the optimal MHE through a new ranking approach. Moreover, some arithmetic operations and properties are extended to GIT2FSs. In addition, to demonstrate its potential applications, the proposed methodology is implemented in a real case study and an illustrative example, and then, the ranking results are compared with those of the others in the literature. Finally, the sensitivity analysis is carried out to show robustness and stability of the obtained results.

Buffer allocation, equipment selection and line balancing optimisation in unreliable production lines

This paper presents an integrated optimisation model to simultaneously solve buffer allocation, equipment selection and line balancing problems in unreliable production line systems. The considered unreliable serial production line consists of m workstations and m − 1 intermediate buffers. The objective is to maximise the system throughput level. A decomposition method is used to estimate the production line throughput. The decision variables in the formulated optimal design problem are buffer levels, types of equipment and the sets of tasks assigned to the workstations. An efficient algorithm, based on the nonlinear threshold accepting algorithm (NLTA) is proposed to solve this problem. The efficiency of the proposed approach is compared to existing algorithms and first tested on a simple assembly line balancing type-2 problem (SALB-2). Here the objective is to minimise the cycle time with a fixed number of workstations. In the second numerical experiment, the integrated model is solved using the NLTA, and its performance is compared to that of the great deluge algorithm (GDA) through several numerical examples. [Received: 9 June 2018; Revised: 15 September 2018; Revised: 18 April 2019; Accepted: 2 August 2019]

Joint Pilot Allocation and Robust Transmission Design for Ultra-Dense User-Centric TDD C-RAN With Imperfect CSI

This paper considers the unavailability of complete channel state information (CSI) in ultra-dense cloud radio access networks. The user-centric cluster is adopted to reduce the computational complexity, while the incomplete CSI is considered to reduce the heavy channel training overhead, where only large-scale inter-cluster CSI is available. Channel estimation for intra-cluster CSI is also considered, where we formulate a joint pilot allocation and user equipment (UE) selection problem to maximize the number of admitted UEs with fixed number of pilots. A novel pilot allocation algorithm is proposed by considering the multi-UE pilot interference. Then, we consider robust beam-vector optimization problem subject to UEs’ data rate requirements and fronthaul capacity constraints, where the channel estimation error and incomplete inter-cluster CSI are considered. The exact data rate is difficult to obtain in closed form, and instead we conservatively replace it with its lower-bound. The resulting problem is non-convex, combinatorial, and even infeasible. A practical algorithm, based on UE selection, successive convex approximation and semi-definite relaxation approach, is proposed to solve this problem with guaranteed convergence. We strictly prove that the semidefinite relaxation is tight with probability 1. Finally, extensive simulation results are presented to show the fast convergence of our proposed algorithm and demonstrate its superiority over the existing algorithms.

System principles and evaluation criteria of reliability for optimization of technological parameters of coal deposits

The article deals with solving the scientific problem of select mining equipment for selection longwall faces of mining venture. The main goal of the paper is to study technology of coal extraction of mining venture. The paper proposes a new approach to solve a problem of mining equipment selection for longwall faces of mining venture. The article describes new method for selection of mining equipment based on theory graph. Special attention is given to technological aspects; they are lenght of longwall faces, depth of coal stratum. Predictions obtained for daily production of mining equipment are compared with design outputs. Conclusions regarding the main reason of instability of longwall faces workings are made. It is found that to be able to use standard algorithms find the shortest path between vertices, you must perform matrix description of the constructed graphs that illustrate the structure of the interaction of different types of control equipment. Using classical optimization of method of discrete mathematics and algorithms for finding the shortest path between two vertices of network models obtained from the formalization of graphs with maximum results of specific types of equipment production chains, solved the problem of rational choice cleaning equipment for the new site with the cost parameters of the mining equipment and cost of mining coal. The authors developed effective and appropriate variants for the mine development for different coal deposits of mining venture.

Excavating and loading equipment for peat mining

Recently, the issues of sustainable development of Russian regions, related to ensuring energy security, are more urgent than ever. To achieve sustainable development, an integrated approach to the use of local natural resources is needed. Practically in all north regions of the Russian Federation, peat as a local natural resource is widespread, which has a practical application in the area of housing services. The paper presents the evaluation of technologies for open-pit peat mining, as well as analysis of technological equipment for peat production. Special attention is paid to a question of peat materials excavating and loading. The problem of equipment selection in a peat surface mine is complex. Many features, restrictions and criteria need to be considered. Use of low and ultra-low ground pressure excavators and low ground pressure front-end loaders with full-range tires to provide the necessary floatation in the peat bog environment is offered.

Constraint programming for solving various assembly line balancing problems

In this paper, the constraint programming (CP) approach is applied for the simple assembly line balancing problem (SALBP) as well as some of its generalizations. CP is a rich modeling language that enables the formulation of general combinatorial problems and is coupled with a strong set of solution methods that are available through general purpose solvers. The proposed formulations are conversions of well-known mixed integer programming (MILP) formulations to CP, along with a new set of constraints that helps the CP solver to converge faster. As a generic solution method, we compare its performance with the best known generic MILP formulations and show that it consistently outperforms MILP for medium to large problem instances. A comparison with SALOME, a well-known custom-made algorithm for solving the SALBP-1, shows that both approaches are capable of efficiently solving problems with up to 100 tasks. When 1000-task problems are concerned, SALOME provides better performance; however, CP can provide relatively good close to optimal solutions for multiple combinations of problem parameters. Finally, the generality of the CP approach is demonstrated by some adaptations of the proposed formulation to other variants of the assembly line balancing problem including the U-shaped assembly line balancing problem and the task assignment and equipment selection problem.

A comparative study of Multi-Objective Algorithms for the Assembly Line Balancing and Equipment Selection Problem under consideration of Product Design Alternatives

A realistic and accurate product cost estimation is of high importance during the design phases of products and assembly lines. This paper presents a methodology that aims at supporting decision makers during the design phases of assembly lines by taking into consideration product designs, processes and resources alternatives. First, we introduce a new variant of the Assembly Line Balancing and Equipment Selection Problem, in which Product Design Alternatives are considered. Since the ability to estimate product costs provides grounds for making better decisions, a new detailed cost model whose aim is to translate the complex and interrelated consequences of product design and manufacturing technologies and processes choice into one single cost metric is proposed. In order to solve the problem under study, 34 Multi-Objective Algorithms were developed. The list of developed algorithms includes variants of Evolutionary Algorithms, Ant Colony Optimisation, Artificial Bee Colony, Cuckoo Search Optimisation, Flower Pollination Algorithm, Bat Algorithm and Particle Swarm Optimisation. The performances of all these algorithms are compared based on fifty well-known problem instances in accordance with four multi-objective quality indicators. Finally, the algorithms are ranked using a nonparametric statistical test.

Equipment Selection by using Fuzzy TOPSIS Method

In this study, Fuzzy TOPSIS method was performed for the selection of open pit truck and the optimal solution of the problem was investigated. Data from Turkish Coal Enterprises was used in the application of the method. This paper explains the Fuzzy TOPSIS approaches with group decision-making application in an open pit coal mine in Turkey. An algorithm of the multi-person multi-criteria decision making with fuzzy set approach was applied an equipment selection problem. It was found that Fuzzy TOPSIS with a group decision making is a method that may help decision-makers in solving different decision-making problems in mining.

Cloud Computation Processing for Oilfield Block Data and Chain Drive Pumping Unit Polished Rod Motion Model

The oil wells are of similar physical parameters but different production parameters in an oilfield block, but selecting the equipment for every well one by one is unpractical. The measured polished rod load data was taken into account in the Fuzzy Clustering C Means algorithm to work out the typical production data, such as polished rod load on the basis of the cloud computing processing for the vast measured polished rod load data in the test wells in a block. The dynamical equation of the chain pumping unit being constructed, the load data are used to simulate the motion of the pumping unit by means of the numerical iteration algorithm. It is shown that the max acceleration does not occur at the up and down dead points in the stroke but at the position about 5–11 ∘ from the dead points. The combination of the typical production data resulting from the cloud computing processing and the numerical iteration algorithm can solve the practical problem of equipment selection and simulation.

Comparison of multi-criteria decision-making methods for equipment selection

Equipment selection is a complex task that requires the consideration of multiple criteria with different measurement units. A number of decision-making methods have been proposed for analysing equipment selection problems, each having their own distinctive advantages and limitations. Despite the number of decision-making techniques available, few comparative studies exist that evaluate two or more methods with a singular problem. This paper evaluates three multi-attribute decision-making methods for an equipment selection problem in the early stages of a chemical manufacturing process. A software framework which incorporates analytical hierarchy process (AHP), multi-attribute range evaluations (MARE) and ELimination Et Choix Traduisant la REalite trois (ELECTRE III) was developed and distributed to a technology manager at Fujifilm Imaging Colorants Ltd (FFIC). The manager, within a team of nine people, examined the same decision problem using the three decision analysis methods. The results of the study are examined in respect to assessing each method’s ability to provide accurate representations of the decision-makers’ preferences and the ability to comprehend the uncertainty present. The decision-makers identified MARE as their preferred method, AHP was found to be comparatively more time-consuming and showed the highest variation of results while ELECTRE III was unable to provide a conclusive best result.

An MILP approach to multi-location, multi-period equipment selection for surface mining with case studies

In the surface mining industry, the Equipment Selection Problem involves choosing an appropriate fleet of trucks and loaders such that the long-term mine plan can be satisfied. An important characteristic for multi-location (multi-location and multi-dumpsite) mines is that the underlying problem is a multi-commodity flow problem. The problem is therefore at least as difficult as the fixed-charge, capacitated multi-commodity flow problem. For long-term schedules it is useful to consider both the purchase and salvage of the equipment, since equipment may be superseded, and there is the possibility of used pre-existing equipment. This may also lead to heterogeneous fleets and arising compatibility considerations. In this paper, we consider two case studies provided by our industry partner. We develop a mixed-integer linear programming model for heterogeneous equipment selection in a surface mine with multiple locations and a multiple period schedule. Encoded in the solution is an allocation scheme in addition to a purchase and salvage policy. We develop a solution approach, including variable preprocessing, to tackle this large-scale problem. We illustrate the computational effectiveness of the resulting model on the two case studies for large sets of equipment and long-term schedule scenarios.