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.

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.