This paper proposes a modified discrete firefly algorithm (DFA) applied to the machine loading problem of the flexible manufacturing systems (FMSs) starting from the mathematical formulation adopted by Swarnkar & Tiwari (2004). The aim of the problem is to identify the optimal jobs sequence that simultaneously maximizes the throughput and minimizes the system unbalance according to given technological constraints (e.g. available tool slots and machining time). The results of the algorithm proposed have been compared with the existing and most recent swarm-based approaches available in the open literature using as benchmark the set of ten problems proposed by Mukhopadhyay et al. (1992). The algorithm shows results that are comparable and sometimes even better than most of the other approaches considering both the quality of the results provided and the computational times obtained.
The research discusses in this paper concerns the improvement allocation policies to reduce the process time in job-shop manufacturing systems. The policies proposed are based on the evaluation of the workload control of the entire manufacturing system. Three policies are proposed: centralized, distributed and proportional. A simulation model is used to test the proposed policies under different conditions as: static and dynamic demand; introduction of machine breakdowns; different level of average manufacturing system utilization. The performance measures are compared to a manufacturing system without policies. The simulation results show that the improvement allocation allows to improve the performance with limited investment (average reduction of process time needed) and how the machine breakdowns and demand changes lead to different better policy. The decision maker can use these results to decide the better policy to use.
From the past decades, increasing attention has been paid to the quality level of technological and mechanical properties achieved by the Additive Manufacturing (AM); these two elements have achieved a good performance, and it is possible to compare this with the results achieved by traditional technology. Therefore, the AM maturity is high enough to let industries adopt this technology in a more general production framework as the mechanical manufacturing industrial one is. Since the technological and mechanical properties are also beneficial for the materials produced with AM, the primary objective of this paper is to focus more on managerial facets, such as the cost control of a production environment, where these new technologies are present. This paper aims to analyse the existing literature about the cost models developed specifically for AM from an operations management point of view and discusses the strengths and weaknesses of all models.
In this paper, an effort has been put to develop a model for estimating growth based on logit re-gression (logit) and implemented the model to Italian manufacturing companies. Our data set consists of 8232 SMEs of Italy. To estimate the growth of the firm an innovative approach that considers annual statements issued the year before the accelerated growth has been considered as the effective estimators of firm growth. The result of the logit showed that return on asset, log (cash flow) and log (Inventory) positively affect in estimating the growth of the high growth firm whereas working capital turnover times negatively affects in estimating the growth of the firm. The discriminant power of the model using Receiver Operating Characteristics curve shows 72.35%, which means the model is fair in terms of estimating the growth.
This paper deals with the total tardiness minimization problem in a parallel machines manufacturing environment where tool change operations have to be scheduled along with jobs. The mentioned issue belongs to the family of scheduling problems under deterministic machine availability restrictions. A new model that considers the effects of the tool wear on the quality characteristics of the worked product is proposed. Since no mathematical programming-based approach has been developed by literature so far, two distinct mixed integer linear programming models, able to schedule jobs as well as tool change activities along the provided production horizon, have been devised. The former is an adaptation of a well-known model presented by the relevant literature for the single machine scheduling problem with tool changes. The latter has been specifically developed for the issue at hand. After a theoretical analysis aimed at revealing the differences between the proposed mathematical models in terms of computational complexity, an extensive experimental campaign has been fulfilled to assess performances of the proposed methods under the CPU time viewpoint. Obtained results have been statistically analyzed through a properly arranged ANOVA analysis.
Facility location models are observed in many diverse areas such as communication networks, transportation, and distribution systems planning. They play significant role in supply chain and operations management and are one of the main well-known topics in strategic agenda of contemporary manufacturing and service companies accompanied by long-lasting effects. We define a new approach for solving stochastic single source capacitated facility location problem (SSSCFLP). Customers with stochastic demand are assigned to set of capacitated facilities that are selected to serve them. It is demonstrated that problem can be transformed to deterministic Single Source Capacitated Facility Location Problem (SSCFLP) for Poisson demand distribution. A hybrid algorithm which combines Lagrangian heuristic with adjusted mixture of Ant colony and Genetic optimization is proposed to find lower and upper bounds for this problem. Computational results of various instances with distinct properties indicate that proposed solving approach is efficient.
Successful flow-shop scheduling outlines a more rapid and efficient process of order fulfilment in warehouse activities. Indeed the way and the speed of order processing and, in particular, the operations concerning materials handling between the upper stocking area and a lower forward picking one must be optimized. The two activities, drops and pickings, have considerable impact on important performance parameters for Supply Chain wholesaler companies. In this paper, a new flow shop scheduling algorithm is formulated in order to process a greater number of orders by replacing the FIFO logic for the drops activities of a wholesaler company on a daily basis. The System Dynamics modelling and simulation have been used to simulate the actual scenario and the output solutions. Finally, a t-Student test validates the modelled algorithm, granting that it can be used for all wholesalers based on drop and picking activities.
Taking tourists’ perspective rather than destination offerings as its core concept, this study introduces “perceived destination brand worldness” as a variable. Perceived destination brand worldness is defined as the positive perception that a tourist has of a country that is visited by tourists from all over the world. Then, the relationship between perceived destination brand worldness and intention to revisit is analyzed using partial least squares regression. This empirical study selects Taiwanese tourists as its sample, and the results show that perceived destination brand worldness is a direct predictor of intention to revisit. In light of these empirical findings and observations, practical and theoretical implications are discussed.
This paper presents a methodology for the design and integration of CONWIP in a make-to-order firm. The approach proposed was applied directly to the flexible job shop of a real manufacturing firm in order to assess the validity of the methodology. After the description of the whole plant layout, attention was focused on a section of the shop floor (21 workstations). The CONWIP system deals with multiple-product families and is characterized by path-type cards and a pull-from-the-bottleneck scheme. The cards release strategy and a customized dispatching rule were created to meet the firm’s specific needs. After the simulation model of the present state was built and validated, the future state to be implemented was created and simulated (i.e. the CONWIP system). The comparison between the two systems achieved excellent results, and showed that CONWIP is a very interesting tool for planning and controlling a complex flexible job shop.
Different criteria are available in the literature to assess the fracture behaviour of sharp V-notches. A typical and well-known criterion is based on the application of the notch stress intensity factors (NSIFs), which are able to quantify the intensity of the stress fields ahead of the notch tip. This work considers two recent energy-based criteria applied here to sharp V-notches. The first criterion is based on the averaged value of the strain energy density (SED), while the second one called Finite Fracture Mechanics (FFM) criterion is available under two different formulations: that by Leguillon et al. and that by Carpinteri et al. Considering the averaged SED criterion, a new expression for estimating the control radius Rc under pure Mode II loading is proposed and compared with the sound expression valid under pure Mode I loading. With reference to pure Mode II loading the critical NSIF at failure can be expressed as a function of the V-notch opening angle. By adopting the three criteria considered here the expressions for the NSIFs are derived and compared. After all, the approaches are employed considering sharp V-notched brittle components under in-plane shear loading, in order to investigate the capability of each approach for the fracture assessment. With this aim a bulk of experimental data taken from the literature is used for the comparison.