Evaluation of the software usability as concerns software alternatives represents a typical Multi-Criteria Decision-Analysis (MCDA) problem. Such a kind of problem can be successfully faced via structured models and approaches which validity have been widely shown in literature. In this work, a methodological framework based on a MCDA model integrating the DEMATEL method along with the ANP technique is proposed and explained with more detail to address the relevant issue of the software usability evaluation. The applicability of the considered DEMATEL-ANP (DANP) based model in the under analysis contest is demonstrated via a preliminary investigation, where the usability of the two major Mobile Operating Systems (MOSs) is compared and quantitatively prioritized. Results of both performed comparison method and sensitivity analysis confirm the validity of the proposed MCDA model as well robustness of its outcomes. Moreover, results obtained point out about the influenced, independent and core factors for the MOSs usability, as well as strengths, weaknesses and discrepancies in the usability as concerns the two investigated alternatives. Representing these outcomes crucial aspects for driving focused MOSs usability improvement processes and strategies, they give also evidence of the effectiveness of the proposed methodological framework.

A single machine batch processing problem with release dates to minimize the total completion time (1|rj,batch|Σ Cj ) is investigated in this research. An original mixed integer linear programming (MILP) model is proposed to optimally solve the problem. Since the research problem at hand is shown to be NP-hard, several different meta-heuristic algorithms based on tabu search (TS) and particle swarm optimization (PSO) are used to solve the problem. To find the most performing heuristic optimization technique, a set of test cases ranging in size (small, medium, and large) are randomly generated and solved by the proposed meta-heuristic algorithms. An extended comparison analysis is carried out and the outperformance of a hybrid meta-heuristic technique properly combining PSO and genetic algorithm (PSO-GA) is statistically demonstrated.

The most used approach to solve tolerance analysis problems for flexible products is the method of influence coefficients that combines the finite element analysis with statistical analysis in order to establish a relationship between the product deviation and part deviation and to foresee the statistical distribution of stresses. The key of this relationship is the sensitivity matrix for the deviations and stresses that can be evaluated by different methods of influence coefficients. Therefore, the aim of this work is to make a review of these methods applying them to evaluate on some single parts the statistical distribution of deviations and stresses due to operating conditions, i.e. due to the displacements applied to the part during its working.

This paper deals with Flow-shop Sequence-Dependent Group Scheduling and worker assignment problem. Flow-shop allows the process of a set of families of products applying the group technology concept to reduce setup costs, lead times, and work-in-process inventory costs. The worker assignment problem deals with assigning workers to workstations considering their different abilities and learning effect. The proposed model in this paper considers different objectives. The decision problems in this cellular manufacturing system are the jobs scheduling within of own group, the group scheduling and the workers assignment to the machines. The aim of this paper is to consider a more realistic profile of heterogeneous workers introducing the learning effect in the joint group scheduling and workers assignment problem. A mathematical model and an evolutionary procedure has been developed to solve this problem. A benchmark of test cases having different numbers of machines, groups, jobs, worker skills and learning index, has been taken into account to compare the efficiency of the proposed algorithm with two well known procedures.

Manufacturing systems need to be able to work under the dynamic and uncertain production environment. Machine and routing flexibility combined with preventive maintenance actions can improve the performance of the manufacturing systems under dynamic conditions. This paper evaluates different levels of machine and routing flexibility combined with different degrees of preventive maintenance policy. The performance measures considered are throughput, work in process and throughput. The performance measures are compared with a system without any flexibility and no preventive maintenance actions. Different levels of flexibility and preventive maintenance actions are examined under a simulation environment. The simulation results highlight more important factors for the performance measures and the best combination of the factors to improve the performance.

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.

This work shows a free-body model for tolerance analysis, that uses the force free-body diagrams and the functional equations’ sensitivities, by simulating the geometrical tolerances together with the dimensional ones. The geometrical tolerances were related to the deviations due to the manufacturing process (i.e. the manufacturing signature). Moreover, weight and friction forces were simulated too. A sensitivity analysis on the developed free body model aimed to evaluate the number of points to discretize the circular bodies and how to calculate the point clouds barycentre in order to reduce the simulation time. A case study was used to exemplify the application of the proposed free-body method with and without considering the manufacturing signature. The results show that the free body model is able to solve assembly problems and the manufacturing signature significantly influences the values of the functional requirement on the product and, therefore, it is impossible to neglect it.

Inappropriate use of gravity and lateral load-bearing system and the use of inappropriate materials may increase in weight of the structure. Thus, we see an increase in gravity and lateral forces and consequently the beam and column dimensions of elements increase. In this paper, by taking several samples of buildings with steel frames and number of different floors and use of different materials as well as various gravity and lateral load-bearing systems this issue was investigated. It was observed that by the use of steel bracing system in both directions of buildings with steel frames; each different load-bearing results in minimum weight loading per unit surface of the skeleton of structure. It was also observed more effect of lightweight construction by increasing the number of floors for all lateral load-bearing systems. Effects of lightweight construction for different lateral load-bearing systems was investigated and we observed that the effects of lightweight construction commonly used for buildings with moment frame system in both directions were more than the rest of the buildings with lateral load-bearing systems.