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Loading in flexible manufacturing systems (FMSs) is affected by the characteristics of the FMS under analysis, by the type of plant where the FMS is introduced, and by the production planning hierarchy where the loading module operates. We propose an analysis of the various aspects that influence the prob- lem formulation, identifying the alternatives available in real systems and possible future evolutions. We then provide a survey of different approaches proposed in the literature to tackle the loading problem. Articles are classified according to the type of FMS analyzed, the objective function, and the constraints. Finally, based on our analysis, we suggest some problem issues which need to be addressed, and also directions for future research.

In the scheduling of manufacturing systems, uncertain events are rather the rule than the exception and are the main responsible of cost increase due to missed due dates, resource idleness, higher work-in-process inventory. Robust scheduling approaches aim at devising schedules insensitive, at least to some degree, to the occurrence of uncertain events. However, robust scheduling must always deal with finding a balanced compromise between expected profit and the protection against extremely unfavorable events having a low occurrence probability. Tackling this problem implies being able of estimating the distribution probability associated with a scheduling objective function, or at least some of its quantiles. In this paper we propose a Markovian approach to estimate the distribution of the completion time of a general network of activities. Grounding on this estimation, an estimation of the objective function distribution can be easily calculated. To demonstrate its viability, the proposed approach is applied to a real industrial case in the machining tool sector.

Computer simulation is widely used to support the design of any kind of complex system and to create computer-generated "virtual worlds" where humans and/or physical devices are embedded (e.g. aircraft flight simulators [20]). However, both the generation of simulation models and the execution of simulations can be time and cost expensive. While there are already several ways to increase the speed of a simulation run, the scientific challenge for the simulation of complex systems still resides in the ability to model (simulate) those systems in a parallel/distributed way [35].

Nowadays De-manufacturing, the processes finalized to the re-manufacturing, re-use and recycling of products and components, is still considered as a minor industry reflecting no-engineered approaches. The unsustainability of actual business models is outstandingly evident for the management of end-of-life of mechatronic devices: their diffusion is quickly increasing and they are largely composed of key-metals and rare earths that could be recovered and re-cycled. Only a new paradigm, where De-manufacturing is considered and practiced by industrial companies at the same extent of manufacturing, should allow a sustainable product life-cycle. This wide challenging target needs a novel multidisciplinary perspective where De-manufacturing business models, system engineering, product design, IT-enabled plant management methods and tools, intelligent automation, process technologies for disassembly, remanufacturing and materials recycling are integrated as the constitutive elements of a new De-manufacturing Factory. Within this scope, this paper critically reviews past research in these areas and outlines future priorities

Long- and medium-term production planning are tools to match production orders with resource capacity and that can also be used as a baseline for material procurement. The lack of a detailed schedule for the manufacturing operations, however, may cause difficulties in providing a proper material requirements planning and may affect the feasibility of the production plan itself. This paper proposes an approach, based on production process knowledge, to extract scheduling information from an aggregate production plan in order to support material procurement. The proposed approach is applied to an industrial case involving machining center production.

Manufacturing systems can be thought as production networks nodes whose relations have a strong impact on design and analysis of each system. Commercial simulators are already adopted to analyse complex networked systems, but the development of a monolithic model can be too complex or infeasible when a detailed description of the nodes is not available outside the 'owner' of the node. Then the problem can be decomposed modelling complex systems with various simulators that interoperate in a synchronized manner. Herein, the integration of simulators is addressed by taking as a reference the High Level Architecture (HLA). This paper proposes modifications to Commercial-off-the-shelf Simulation Package Interoperability Product Development Group protocols and to use patterns of how HLA can be effectively adopted to support Commercial Simulation Package interoperability: a new solution for the synchronous entity passing problem and modifications to the Entity Transfer Specification are presented. The resulting infrastructure is validated and tested over an industrial case. Journal of Simulation (2012) 6, 237-252. doi:10.1057/jos.2012.6; published online 15 June 2012

The work gives a classification of the various “Single Shot heuristics” proposed in the literature for the solution of the Static Permutation Flowshop (SPF) problems. It then tries to compare their performances and draw a ranking. Since the ranking cannot be univocal, the aim is to show how it is affected by various elements that characterize a SPF problem (objective function, number of jobs, number of machines, processing time matrix). The final purpose is to give some guidelines for the choice of the proper algorithm on the basis of the specific “environmental conditions” in which the algorithm will operate.

Capri, Naples (Italy)

Nel corso del tempo, l'automazione nei contesti produttivi si è evoluta da automazione rigida, in cui le macchine operatrici eseguono automaticamente singole operazioni e/o movimentazioni ripetute a tempo indeterminato, ad un'automazione fl essibile, in cui le macchine operatrici eseguono un numero crescente, anche se fi nito, di varianti nelle operazioni e nei cicli. Alla base di entrambi i paradigmi troviamo sempre l'ipotesi che tutte le incertezze di prodotto, processo, materiale, ambiente, strumenti e informazioni possano essere eliminate prima di implementare con successo un sistema automatizzato. Là dove tale condizione non è rispettata,si continuano ad utilizzare processi produttivi manuali o mediati dalla supervisione di operatori umani. Di fronte ai costi del lavoro relativamente alti e alla potenziale mancanza di lavoratori specializzati, l'Europa deve e dovrà sempre di più affi darsi a macchine operatrici in grado di operare autonomamente e in modo affi dabile in contesti non completamente noti a priori e con range di varianti nelle operazioni sempre meno limitati. Al concetto di supervisione da parte dell'operatore dovrà inoltre sostituirsi un concetto di cooperazione tra operatore e macchina operatrice autonoma. A lungo termine, le macchine operatrici dovranno pertanto evolvere verso profi li di applicazione sempre più knowledge based e per certi aspetti "umani". Questa evoluzione "naturale" dovrà poi essere mediata, o meglio resa compatibile, con una serie di condizionamenti, primi fra tutti quelli provenienti dalla legislazione in materia di sicurezza, salute ed ambiente che, in Europa più che altrove, vincolano fortemente alcune scelte tecnologiche. Due esempi paradigmatici vengono di seguito illustrati nel settore delle macchine agricole e movimento terra e nel settore della robotica industriale.

The paper proposes a decomposition method for evaluating the performance of transfer lines where machines can fail in multiple modes and can be repaired with non-exponential times. Indeed, while times to machine failure can be often modeled using exponential distributions with acceptable accuracy, times to repair are very rarely observed to be exponentially distributed in actual systems. This feature limits the applicability of existing approximate analytical methods to real production lines. In this paper, the discrete acyclic phase-type distribution is used to model the repair process, for each failure mode of the machines composing the system. The exact analysis of the two-machine system is used as a building block for the decomposition method, proposed to study multi-stage lines. Numerical results show the high accuracy of the developed method in estimating the average throughput and buffer levels.

International audience; In Manufacturing-to-Order or Engineering-to-Order systems producing complex and highly customized items, each item has its own characteristics,which are often tailored for a specific customer. Project scheduling approaches are suitable for production planning in such environments. However, when we consider the production of complex items, the distinct production operations are often aggregated into activities representing whole production phases. In such cases, the planning and scheduling problem works on the aggregate activities, considering that, in most cases, they also have to be manually executed. Moreover, simple finish-to-start precedence relations no longer correctly represent the real production process, but overlapping among activities should be allowed. In this paper, a project scheduling approach is proposed for production planning in Manufacturing-to-Order systems. The Variable Intensity formulation is used to allow the effort committed to the execution of activites to vary over time. Feeding precedences are developed to model generalized precedence relations when the execution mode of activities is not known a priori. Two mathematical formulations of these precedence relations are proposed. The formulations are applied both to random generated instances and to an industrial system producing machining centers and are compared in terms of computational efficiency.

This paper presents an analytical method for evaluating the performance of production systems, jointly considering in a unique framework quality and production logistics performance measures. In the literature, quality and production logistics have traditionally been investigated using independent approaches. Thus far, only a few recent contributions have focused on their mutual inter-relation, showing that benefits can be achieved from an integrated analysis. This paper contributes to this growing research by considering, for the first time, production systems in which the behaviour of the machines is monitored by statistical control charts. The control action performed by the quality control system on the machines is directly modeled. Moreover, the impact of the quality control action on the logistic flow of parts in the system is taken into account. In order to estimate the performance of such systems, an approximate analytical method based on the system decomposition technique is developed. The accuracy of the method is assessed by comparing the results with those obtained by simulation. Analysis of the results provides new insights into the relations among the quality and production logistics performance measures and paves the way to the development of integrated design techniques for improved configurations of the system as a whole.

Manufacturing systems can be thought as production networks nodes whose relations have a strong impact on design and analysis of each system. One of the most common techniques to support these tasks is Discrete-Event Simulation. The state-of-the art commercial simulators are already adopted to analyze complex networked systems, but the development of a monolithic simulation model can be too complex or even infeasible when a detailed description of the nodes is not available outside the "owner" of the node. In these cases the problem can be decomposed by modeling complex systems with various simulators that interoperate in a synchronized manner. Herein, the integration of simulators is addressed by taking as a reference the High Level Architecture (HLA) and the research carried out by Commercial-off-the-shelf Simulation Package Interoperability (CSPI) Product Development Group (PDG). This paper proposes modifications to CSPI-PDG protocols and to use patterns of how HLA can be effectively adopted to support CSP interoperability: a new solution for the synchronous entity passing problem and a modification to the Entity Transfer Specification are presented. The resulting infrastructure is validated and tested over a realistic industrial case. © 2011 IEEE.

In the aerospace production industry, the advent of composite materials has had a huge impact on the problem of designing and managing production systems which embed different technologies for the manufacture of complex products. One critical issue is the evaluation of the capability of the resources operating in the manufacturing environment, such as machines, robots and auxiliary devices, across the system lifecycle. During the system design phase having a crystal clear view of the resource capabilities enables the selection of the best set of resources that match the production requirements; also during the system control and management phases, the evaluation of nominal and actual resource functional characteristics allows real-time response to unforeseen events. The research proposed in this paper aims at providing a STEP compliant schema entitled the AeroFRAME knowledge based schema, to represent geometric and functional information on products, processes and systems for the aerospace industry. The paper concludes with an application of a real manufacturing scenario in which new families of manufacturing resources such as Prepreg Cutting Machines, Filament Winding Robots and Automatic Tape Placement machines are represented by the schema.

Process planning is an important and time-consuming activity that highly depends on the experience of process planners. In order to reduce the required time and to support the planner, CAPP systems are getting central feature of setup planning, operation sequencing and pallet configuration. This paper fits in CAPP approach for the definition of the operations optimal sequence to machine all workpieces mounted on a pallet on a 4-axes machine tool. An algorithm and a mathematical model yield a user-friendly, quick and repeatable method for the definition of the operations sequence on the basis of a non-productive times minimization criteria. Three post-processors analyze the proposed solution to reduce the gap from optimality. A real test case is presented.

In this paper an innovative approach to develop manufacturing simulation models, refereed as UMSIS - UML Modeled SIMANO Implemented Simulation software -, is presented. The goals of the proposed approach are the definition of an object-oriented environment UML based to model highly automated manufacturing production systems and a method to translate the UML model into a process oriented simulation model. Since the UMSIS approach possesses both the characteristics of object-oriented models and of a straightforward mapping between high-level conceptual models and process-oriented simulation models, the time required to design and develop a new simulation model or to modify an existing one will be notably reduced. In the paper the proposed approach has been applied to design a simulation model of a control module of a real flexible manufacturing system. The model simulates the control software that manages the pallet flow in the reference FMS.

Product life cycle design - Generating sustainable product life cycles explains the importance of a holistic long-term planning and management approach to reaching a maximum product benefit over the entire life cycle. The paradigm of thinking in product life cycles supports manufacturers in shaping successful products. The book promotes various methods and tools for life cycle management and merges them into an integrated planning approach. In this monograph Europe's leading academic experts in the field of life cycle management have consolidated their expertise. Readers will learn about different tools and methods for life cycle modelling and digital information support. Industrial examples show how a consistent product data management with closed-loop information cycles enables manufacturers to activate the hidden performance potentials of their products and in their production lines. In this respect Product life cycle design also illustrates the benefits of a networked production including integrated product service systems and innovative business models, and presents methods for evaluating the economic and ecological impacts of life cycle design, highlighting them with practical examples. The book addresses professionals as well as researchers and students from the field of life cycle management. Practitioners and researchers pursuing life cycle excellence will benefit from the comprehensive coverage of methods and various examples from industry.

The continuing drive towards an increasing degree of products customization leads companies to produce individual highly personalized items according with customer requirements. Therefore, the ability to generate accurate and timely offers has become a critical successful factor, because it has an impact on the profitability of the possible contract. This paper takes in consideration the quote generation process for special tools and the knowledge engineering as possible solution to the problem. A new approach in the field of CAPP and AI is proposed. This method is based on an ontology of knowledge representation and on problem solving techniques; it automatically defines the work cycle for the realization of the tool, in terms of times and costs. The authors have tested the proposed approach on real industrial cases of quoting for special tools, obtaining good results.

Manufacturing flexibility is seen as the main mechanism for surviving in the present market environment. Companies acquire systems with a high degree of flexibility to cope with frequent production volume changes and evolutions of the technological requirements of products. However, literature and industrial experience show that flexibility is not always a well-defined concept. Therefore it is really complex to understand and use flexibility during system design process. Indeed, the development of structured approaches to support the system design by considering basic flexibility forms is still an open issue. This work presents an Ontology on Flexibility aiming at providing a standard method to analyze flexibility. Firstly, it contributes in systemizing the large number of existing flexibility definitions and classifications. Secondly, it can be used to analyze real systems and to better understand their characteristics in terms of flexibility. Finally this ontology represents a key point of a general approach to design production system with the right level of flexibility.

The topic of manufacturing flexibility has been addressed by many scientific contributions in the past years, thus highlighting the relevance of the problem both at industrial and academic level. Internal and external issues need to be faced at the same time when designing a manufacturing system and its flexibility; indeed, products and processes are easily and frequently changed by market and manufacturing strategies, while production systems must cope with relevant inertia which slow down their changes. Therefore, a fundamental issue consists of filling the modeling gap between a production problem and the manufacturing system best suited to face it. Current literature provides a huge research on the analysis of flexibility, as a solution to cope with uncertainty in the market and to support the manufacturing strategy. However, the link between the need of flexibility and the design of manufacturing systems is still weak. This need includes a deeper understanding of the nature of flexibility and, in turn, a clear definition of the dimensions of flexibility. This chapter reviews the state of the art of the literature on manufacturing flexibility by proposing also a conceptual framework for its formalization.

Competitive companies decide to invest in manufacturing flexibility in order to guarantee to production systems the robustness required to face product changes. On the other hand, manufacturing flexibility costs can jeopardize system profitability. Therefore, to design a cost-effective and responsive system the flexibility degree needs to be tuned on production problems. For this purpose, a new class of manufacturing systems named Focused Flexibility Manufacturing Systems (FFMSs) is proposed. FFMS is characterized by the minimum level of flexibility required to face production problems with the minimum System Investment Cost over the system lifecycle. The aim of this paper is to propose a FFMS design approach based on a Two Stage Mixed Integer Stochastic Programming Problem. The output of the FFMS design approach is the type and number of devices to be purchased, in terms of machines, load/unload stations and carriers. A comparison between FMS and FFMS costs has been carried out taking as reference a real production case.

This chapter introduces a conceptual framework for the integrated modeling of product, process and production system data. The work focuses on the Manufacturing System Design problem and aims at providing a common data structure as a reference for different methodologies and tools in this domain. The framework is flexible, extendible, scalable and has been developed as an object-oriented model by means of UML (Unified Modeling Language). Moreover, the proposed data model can have a wider applicability since it is based on shared standards and previous general frameworks. The concept of evolution has been introduced into the model, since it is essential to include market uncertainty in the design of competitive production systems. Finally, the developed framework has been translated into a relational database which can be interfaced with all the main phases of the system design approach presented in this book.

Manufacturing Flexibility is seen as the main answer for surviving in markets characterized by frequent volume changes and evolutions of the technological requirements of products. However, the competitiveness of a firm can be strongly affected by capital intensive investments in system flexibility. This chapter presents an approach to design new manufacturing system architectures endowed with the right level of flexibility required by the specific production problem. These systems are named Focused Flexibility Manufacturing Systems (FFMSs). The key idea consists in tuning system flexibility on the production problem to cope with uncertainty related to the evolution of product demand. The significance of this topic and its potential impact on the industrial sector in the medium-long run is testified by the interest shown by companies making initial efforts in this field.

Manufacturing systems design must provide effective solutions to cope with the demand during the whole system life-cycle. The problem consists of selecting the appropriate set of resources which best fits the requirements of the addressed production problem. When the demand is characterized by a family of products undergoing technological and volume modifications, the system design process becomes quite complicated. Starting from present and forecasted information, machine tool builders have to design systems endowed with the flexibility and reconfigurability levels that enable the system to face the production problem variability during its life. In spite of the relevance of this topic, there is a lack of tools to explicitly design system flexibility and reconfigurability considering the uncertainty affecting the problem. By addressing two main types of uncertainty, i.e. demand variability and resource availability, this chapter presents a solution method based on multi-stage stochastic programming, to support the design of new manufacturing system architectures whose level of flexibility is focused on the specific production requirements. The problem variability is modeled through scenario trees and the solution is a capacity plan with an initial system configuration and possible reconfigurations. Testing experiments have been carried out considering an industrial case to study the benefits that this approach can offer to machine tool builders.

The present work proposes a conceptual reference framework for the integrated modeling of product, production process and system data. The framework is flexible (easily adaptable to different production contexts), extendible and scalable (in terms of levels of details) and integrated (products, processes and systems are all considered and described). The framework has been developed as an object-oriented model by means of the UML (Unified Modeling Language) defacto standard. In particular, the class diagram of this UML model, representing the core portion of the framework, is described in detail. The conceptual reference framework was developed to support both researchers and industrialists – in different manufacturing domains – in the modeling activities behind their problem solving methodologies, also aiding them in exactly modeling the information they need. The basic idea behind the work is that a more effective use of the heterogeneous decision support methods, normally employed at the different enterprise levels, can be obtained if these methods are based a common conceptual model. The first two applications of the proposed reference framework are also described in the final sections.