Product Configuration

The emergence of the concept of smart contracts provides great opportunities to automatize the performance of contractual relations and make it reliable. In the product configuration domain, the smart contract development is an independent task that is not related to the development of a product usage of which the smart contract regulates. A conceptual framework combining ontology-based product configuration to create service bundles with semantic rules formalizing smart contracts to regulate the automated service provisioning/consumption closes the gap between the product development and its contractual use. The contribution of the present paper is architecture for a decision support system to be built according to the conceptual framework. An application scenario from the domain of providing Internet services illustrates interactions between the architectural components.

Product Configuration Systems (PCS) is a step in the direction of mass customization in the sense that PCS allows a firm to significantly lower the unit cost of configuration. Thus PCS is a valuable technology for lowering operating costs while ...

Feature modeling is an important approach to dealing with variability at an abstract level in a hierarchical manner extensively used in software product lines. For its use in conjunction with other UML models and MDA approach, it is important to correctly integrate feature modeling into UML. In this paper, we present an approach to integrating feature modeling into UML that respects abstractness of feature modeling elements. This is achieved by deriving feature modeling elements from the deeper levels of the UML metamodel. We applied this approach to the essential elements of feature modeling in the cardinality-based Czarnecki-Eisenecker notation and selected elements specific to other notations. Since UML modeling tools do not support such modifications of the UML metatmodel, in order to facilitate experimentation with combining elements from different notations, we implemented this feature modeling extension as a UML profile (in Enterprise Architect and Omondo UML).

Firm-specific technological competencies help explain why firms are different, how they change over time, and whether or not they are capable of remaining competitive. Data on more than 400 of the world's largest firms show that their technological competencies have the following characteristics: 1. They are typically multi-field, and becoming more so over time, with competencies ranging beyond their product range, in technical fields outside their 'distinctive core'. 2. They are highly stable and differentiated, with both the technology profile and the directions of Iocalised search strongly influenced by firms' principal products. 3. The rate of search is influenced by both the firm's principal products, and the conditions in its home count~. However, considerable unexplained variance suggests scope Jbr managerial choice. These findings confirm the importance of complexi~, and path dependency in the accumulation of firm-specific technological competencies, and show that managers are heavily constrained in the directions of their technological search. They also show the limits of the notion of competition through variety, given that the same specific field of technological competence is often essential to the development of a range of possible product configurations, Technological imperatives still exist, © 1997 Elsevier Science B.V.

Enantioselective syntheses of organosulfur compounds via [2,3] sigmatropic rearrangements of ylides derived from di(allyl), di(propargyl), and di(benzy1) sulfide complexes; control of carbon configuration by an easily resolved and recycled rhenium auxiliary

General Motors faces probably the most complex Systems and Software Product Line Engineering (PLE) challenges ever, in terms of product complexity, richness of variation, size of organization, and an unforgiving requirement to support over a dozen simultaneous development streams all geared towards each new model year. To meet this challenge, GM turned to an advanced set of explicitly defined product line engineering solutions, which have been referred to as Second Generation PLE (2GPLE). This includes reliance on features as the lingua franca to express product differences in all phases of the lifecycle, deeply nested hierarchical product lines, industrial strength automation to provide modeling consistency throughout, and more. This paper explains how 2GPLE is being applied at General Motors, and the technical and organizational lessons learned so far.

Product Configuration Systems (PCS) is a step in the direction of mass customization in the sense that PCS allows a firm to significantly lower the unit cost of configuration. Thus PCS is a valuable technology for lowering operating costs while ...

The large number of configurations that a feature model can encode makes the manual analysis of feature models an error prone and costly task. Then, computer-aided mechanisms appeared as a solution to extract useful information from feature models. This process of extracting information from feature models is known as ''Automated Analysis of Feature models'' that has been one of the main areas of research in the last years where more than thirty analysis operations have been proposed. In this dissertation we looked for different tendencies in the automated analysis field and found several research opportunities. Driven by real-world scenarios such as smart phone or videosurveillance domains, we contributed applying, adapting or extending automated analysis operations in variability intensive systems evolution, testing and configuration.

1Companies’ reports indicate a mixture of success and failure in Product Configuration Systems (PCS) projects. Moreover, the attention paid to PCS across different industries is increasing. Therefore, more studies are needed to analyze risks, costs, and benefits of PCS. This paper uses real case projects to demonstrate the cost-benefit analysis of PCSs in real industrial setups. Hence, this article quantifies savings in terms of reduced working hours, and the cost implications with reference to development, implementation, and maintenance. The study fills the gap in previous research by addressing what the influence of other factors on gained cost-benefits from PCSs are likely to be. This study aims to explain why some PCS projects are more costeffective than the others. While there are a number of factors affecting the cost-benefit analysis in PCS, the focus of this study remains mainly on the number of users and complexity of the project. The comparison in the case studies reveale...

Feature models are used in member product configuration in software product lines. A valid product configuration must satisfy two kinds of constraints, multiplicity of each variation point and dependencies among the variants in a product line. The combined impact of the two kinds of constrains on product configuration should be well understood. In this paper we propose a measurement, called V ariationRank, that combines the two kinds of constraints to assess the complexity of variation points in software product lines. Based on the measurement we can identify those variation points with the highest impact on product configurations in a product line. This information could be used as guidance in product configuration as well as for feature model optimization in software product lines. A case study is presented and discussed in this paper as well.

Work is identified as a major obstacle to the installation of young farmers or the continued activity of many farmers, in particular in livestock farming because of the obligations associated with the daily care of the animals. Work and its variations at farm scale (economy, organisation, value, efficiency, hardness of the work…) cover a multiplicity of questions and mobilize multidisciplinary approaches which take into account the singularity of the livestock farmer's view of his work. Evolutions in the role of advisers, their skills and position regarding farmers, have been necessary. In France, the attention given to this theme has for several years been the subject of a partnership between Research, Development and Education, which has taken shape today within the framework of a network officially approved by the Ministry of Agriculture. This "Work on livestock farms" network (WLFN) is the special framework to structure the sharing of experience and the emergence of new synergies. The genesis of the WLFN, its activities and productions (tools for advice, references, teaching work, analyses of experiences, etc), widely circulated, are presented and illustrated in the text. We show how the maturation of the partnership has been accompanied by maturation in the way of tackling this subject: the approaches of livestock farming systems (LFS) research and social sciences have converged; the question of advice (tools and approaches) has been reaffirmed. New interactions are engaged in the WLFN at the crossing of changes in work and the technical changes imposed by production and environmental issues.

Software product lines are used to develop a set of software products that, while being different, share a common set of features. Feature models are used as a compact representation of all the products (e.g., possible configurations) of the product line. The number of products that a feature model encodes may grow exponentially with the number of features. This increases the cost of testing the products within a product line. Some proposals deal with this problem by reducing the testing space using different techniques. However, a daunting challenge is to explore how the cost and value of test cases can be modelled and optimized in order to have lower cost testing processes. In this paper, we present TESting vAriAbiLity Intensive Systems (TESALIA), an approach that uses automated analysis of feature models to optimize the testing of variability intensive systems. We model test value and cost as feature attributes and then we use a constraint satisfaction solver to prune, prioritize and package product line tests complementing prior work in the software product line testing literature. A prototype implementation of TESALIA is used for validation in an Android example showing the benefits of maximizing the mobile market-share (the value function) while meeting a budgetary constraint.

Mass customization refers to the increase in variety and customization of the manufactured products and services. It is now economically feasible thanks to the availability of computer-aided manufacturing systems, which allow people to customize standard products, and to Internet, through which many online retailers now operate, thus eliminating the constraints of physical shelf space and other bottlenecks of distribution that, in past years, prevented the production of niche products because of their high production costs. To permit mass customization, several software-based product configurators are available on the Web: they guide people in adapting a product to their needs and desires. A drawback of such configurators is the limited range of changes permitted. We present in this paper a system that gives people more freedom in creating products that best fit their desires, thanks to the use of an ontology, which models the possible product compositions that users can perform. The proposed solution is shown through a case study, which refers to furniture production.

Models of configurable products can have hundreds of variables and thousands of configuration constraints. A product engineer usually has a limited responsibility area, and thus is interested in only a small subset of the variables that are relevant to the responsibility area. It is important for the engineer to have an overview of possible products with respect to the responsibility area, with all irrelevant information omitted. Configurations with some variables omitted we will call partial configurations, and we will call a partial configuration ...

Some of the recent proposals of web-based applications are oriented to provide advanced search services through virtual shops. Within this context, this paper proposes an advanced type of software application that simulates how a sales assistant dialogues with a consumer to dynamically configure a product according to particular needs. The paper presents the general knowledge model that uses artificial intelligence and knowledge-based techniques to simulate the configuration process. Finally, the paper illustrates the description with an example of an application in the field of photography equipment.

Robotic systems are becoming common in different domains and for various purposes, such as unmanned aerial vehicles performing search and rescue operations, or robots operating in manufacturing plants. Such systems are characterized by close interactions, or even collaborations, between hardware and machinery on the one hand, and humans on the other. Furthermore, as Cyber-Physical Systems (CPS) in general and robotic applications in particular typically operate in an emergent environment, unanticipated events may occur during their operation, making the need for runtime monitoring support a crucial yet often time-consuming task. Runtime monitoring typically requires establishing support for collecting data, aggregating and transporting the data to a monitoring framework for persistence and further processing, and finally, performing checks of functional and non-functional properties. In this paper, we present our initial efforts towards a flexible monitoring framework for ROS-based systems. We report on challenges for establishing runtime monitoring support and present our preliminary architecture that aims to significantly reduce the setup and maintenance effort when creating monitors and establishing constraint checks. CCS CONCEPTS • Computer systems organization → Robotics.

Increasing competition and fast innovation take up new challenges for engineer-to-order (ETO) companies to address special requests from customers without losing efficiency. The optimization of the trade-off between customization and operational efficiency is a core competence for ETO manufacturers. Most advanced companies are reacting by introducing an ETO Enabling Process, which is the process of transforming special requests alongside the ETO value chain into know-how to be subsequently reused with a gain in productivity. This paper, therefore, presents relevant best practices implemented within a research project with three ETO companies while adapting the ETO Enabling Process to their specific organizational settings.

In this study, exothermic reaction of methanol synthesis is coupled with endothermic reaction of dehydrogenation of cyclohexane in a two-packed bed reactor in order to simultaneous production of hydrogen, methanol and benzene. Steady-state, heterogeneous model predicts the performance of this configuration. The simulation results for co-current and counter-current modes in thermally coupled methanol reactor (TCMR) are investigated and compared with data of an industrial scale conventional methanol reactor (CMR) with same feed conditions. In addition, the variation of different operating parameters along the reactor has been considered. The simulation results represent 1.89 % enhancements in methanol recovery yield of co-current mode in TCMR in comparison with CMR. Also, results show that hydrogen recovery yield in dehydrogenation of cyclohexane side in co-current and counter-current modes of TCMR is equal to 2.352 and 2.255, respectively. Finally, TCMR in cocurrent mode is a feasible reactor for cost reduction because it has benefits such as production of multiple products, enhancement of productivity by shifting equilibrium of reactions to forward, large savings in the operational and capital costs, compact and efficient process.

In this study, exothermic reaction of methanol synthesis is coupled with endothermic reaction of dehydrogenation of cyclohexane in a two-packed bed reactor in order to simultaneous production of hydrogen, methanol and benzene. Steady-state, heterogeneous model predicts the performance of this configuration. The simulation results for co-current and counter-current modes in thermally coupled methanol reactor (TCMR) are investigated and compared with data of an industrial scale conventional methanol reactor (CMR) with same feed conditions. In addition, the variation of different operating parameters along the reactor has been considered. The simulation results represent 1.89 % enhancements in methanol recovery yield of co-current mode in TCMR in comparison with CMR. Also, results show that hydrogen recovery yield in dehydrogenation of cyclohexane side in co-current and counter-current modes of TCMR is equal to 2.352 and 2.255, respectively. Finally, TCMR in cocurrent mode is a feasible reactor for cost reduction because it has benefits such as production of multiple products, enhancement of productivity by shifting equilibrium of reactions to forward, large savings in the operational and capital costs, compact and efficient process.

A Sustainable Supply Chain (SSC) is required to consider Environmental, Economic and Societal needs equally and in tandem. SSCs are super systems that is made up of multiple interconnected forward and reverse business processes which relays and relies on resources and information from one another. There are only a few techniques that are able to model such complex relationship, and among the best is the IDEF family of techniques. There are also variations to these core techniques which specifically model End-of-Life Vehicle (ELV) recovery, and there is also a hybrid technique which allows a single IDEF technique is used for modeling, instead of using a number of complementing techniques which is the norm. In this study, these two variation techniques are merged and further refined to allow it to model sustainability elements which was missing in any core technique or its variation. This proposed technique is called Enhanced IDEF-SIM (EnIS) and will provide a novel way to model and understand the infrastructure of complete SSCs.

In current business environment many OEM companies are employing mass customization strategy, which has implication on the entire operations of an enterprise and especially influences the character of assembly processes. Increased product differentiation in context of customized production causes significant changes in complexity of assembly systems. Our focus in this paper is the development of methodological framework for generating all possible product configurations based on number of stable and optional components or modules from which a final product is completed. Subsequently, we propose an approach to determining so called product configuration complexity by specifying classes and sub-classes of product configurations. Then, for each sub-class of product configuration we can obtain upper bounds values of configuration complexity. Finally, configuration complexity scale based on the obtain upper bounds values is outlined and discussed.

Aims: This study presents the first structural model and proposed the identity of four important key amino acid residues, Asp13, Arg51, Ser131 and Asp207 for the stereospecific haloalkanoic acid dehalogenase from Rhizobium sp. RC1. Methodology and results: The enzyme was built using a homology modeling technique; the structure of crystallized L-DEX YL from Pseudomonas sp. strain YL as a template. Model validation was performed using PROCHECK to generate the Ramachandran plot. The results showed 80.4% of its residues were located in the most favoured regions suggested that the model is acceptable. Molecular dynamics simulation of the model protein was performed in water for 10 nanoseconds in which Na + was added to neutralize the negative charge and achieved energy minimization. The energy value and RMSD fluctuation of Cα backbone of the model were computed and confirmed the stability of the model protein. Conclusion, significance and impact of study: In silico or computationally based function prediction is important to complement with future empirical approaches. L-haloacid dehalogenase (DehL), previously isolated from Rhizobium sp. RC1 was known to degrade halogenated environmental pollutants. However, its structure and functions are still unknown. This structural information of DehL provides insights for future work in the rational design of stereospecific haloalkanoic acid dehalogenases.

With an increasing number of cloud computing offerings in the market, migrating an existing computational infrastructure to the cloud requires comparison of different offers in order to find the most suitable configuration. Cloud providers offer many configuration options, such as location, purchasing mode, redundancy, extra storage, etc. Often, the information about such options is not well organised. This leads to large and unstructured configuration spaces, and turns the comparison into a tedious, error-prone search problem for the customers. In this work we focus on supporting customer decision making for selecting the most suitable cloud configuration-in terms of infrastructural requirements and cost. We achieve this by means of variability modelling and analysis techniques. Firstly, we structure the configuration space of an IaaS using feature models, usually employed for the modelling of variabilityintensive systems, and present the case study of the Amazon EC2. Secondly, we assist the configuration search process. Feature models enable the use of different analysis operations that, among others, automate the search of optimal configurations. Results of our analysis show how our approach, with a negligible analysis time, outperforms commercial approaches in terms of expressiveness and accuracy.

The applicability of manufacturing planning and control methods differs between environments. This paper explains the fit between the planning environment and material and capacity planning on the detailed material planning and shop‐floor planning levels. The study is based on a conceptual discussion and a survey of 84 Swedish manufacturing companies. Results show the use of planning methods and their levels of user satisfaction in complex customer order production, configure to order production, batch production of standardized products and repetitive mass production, respectively.

Product-Service Systems (PSS) are being revolutionized into smart, connected products, which changes the industrial and technological landscape and unlocks unprecedented opportunities. The intelligence that smart, connected products embed paves the way for more sophisticated data gathering and analytics capabilities ushering in tandem a new era of smarter supply and production chains, smarter production processes, and even end-to-end connected manufacturing ecosystems. This vision imposes a new technology stack and lifecycle models to support and capacitate smart, connected products and services. The main contribution of this article is a novel PSS customization lifecycle methodology with underpinning technological solutions that enable collaborative on-demand PSS customization by supporting companies to evolve their product-service offerings by transforming them into smart, connected products. This is facilitated by the proposed lifecycle through formalized knowledge-intensive structures and associated IT tools that provide the basis for actionable PSS and production "intelligence" and a move toward more fact-based manufacturing decisions. The basic building blocks of the proposed PSS customization lifecycle and its technological stack are implemented in an integrated tool-suite and validated via large-scale industrial case studies. The PSS customization lifecycle described in this paper, paves the way for a new direction in highly-connected, knowledge-enabled smart factories, where devices, production equipment, production processes, and human-operators are connected, offering decision-making support on the basis of production knowledge and data.

Models of configurable products can have hundreds of variables and thousands of configuration constraints. A product engineer usually has a limited responsibility area, and thus is interested in only a small subset of the variables that are relevant to the responsibility area. It is important for the engineer to have an overview of possible products with respect to the responsibility area, with all irrelevant information omitted. Configurations with some variables omitted we will call partial configurations, and we will call a partial configuration valid if it can be extended to a complete configuration satisfying all configuration constraints. In this paper we consider exact ways to compute valid partial configurations: we present two new algorithms based on Boolean satisfiability solvers, as well as ways to use knowledge compilation methods (Binary Decision Diagrams and Decomposable Negation Normal Form) to compute valid partial configurations. We also show that the proposed methods are feasible on configuration data from two automotive companies.

In the development of complex products product configuration systems are often used to support the development process. Item Usage Rules (IURs) are conditions for including specific items in products bills of materials based on a high-level product description. Large number of items and significant complexity of IURs make it difficult to maintain and analyze IURs manually. In this paper we present an automated approach for verifying IURs, which guarantees the presence of exactly one item from a predefined set in each product, as well as that an IUR can be reformulated without changing the set of products for which the item was included.

Models of configurable products can have hundreds of variables and thousands of configuration constraints. A product engineer usually has a limited responsibility area, and thus is interested in only a small subset of the variables that are relevant to the responsibility area. It is important for the engineer to have an overview of possible products with respect to the responsibility area, with all irrelevant information omitted. Configurations with some variables omitted we will call partial configurations, and we will call a partial configuration ...

Digital technologies enable apparel manufacturers to unlock solutions for new product development (NPD) challenges faced during the Covid-19 pandemic. A Product Configurator (PC) is the key to Mass Customization (MC) as it can employ to elicit customer requirements, which is essential in successful NPD. Even though some online PCs exist in apparel retail and product development, no one could gather customer requirements and deploy them in the NPD. This paper conceptualizes a Natural Language Processing (NLP)-based PC on eliciting customer requirements based on a systematic literature review and a basic concept of Design Space Analysis. Finally, it is contended that this knowledge can apply in relevant software development to modernize apparel design, development and online retail.

Customers in B2B as well as B2C markets increasingly demand integrated problem solutions from their suppliers, comprising both physical artefacts (products) and services. Applying a mixed bundling strategy to offer such value bundles to customers foremost requires a sound configuration and economic calculation of value propositions, based on previously defined modules of products and services. In this paper, a modelling language is introduced to describe the function and structure of such modules, as well as to calculate the economic consequences of value propositions on a customer-individual level. The proposed modelling language has been embedded into a software tool to evaluate its utility regarding the customization and offering of integrated value bundles to customers.

In this work, a product centric view of the design process is used in capturing the process and the design knowledge of complex, hierarchical engineering systems. The use of individual product configurators expedites redesign and further exploration of the design space. The notion of concept representation is introduced to mathematically formulate the various aspects of a product concept. This representation also enhances the understanding of the overall objectives, allowing for design sensitivity analyses, pre-computation of the engineering design spaces and multi-disciplinary constraint management between modules. Product configurators are developed in a distributed framework to enable rapid design across different platforms. The Purdue Formula SAE vehicle is used as an example case in developing the configuration problem.

1 Product Configuration Systems (PCS) are increasingly used by companies to automate the performance of the sales and engineering processes. Since the benefits from such projects have huge variations, it is crucial to make the right decisions when scoping and developing PCSs. The development of PCS is influenced by both business interests and technical insights. Developers of PCS face various challenges while working in team, including different stakeholders such as business owners, developers, project managers, and product experts. The more diverse the team is, the more significant are the challenges. This paper suggests that Behavior-driven Development (BDD) may provide configuration teams with a specific structure to express scenarios (and thus constraints) on PCS in natural language. BDD may yield benefits such as a better expression of PCS constraints, more efficient communication of requirements and incorporation of the expressed rules in a software transformation process. In ...

We study a complex Configured to Order (CTO) business operating under variable product configuration recipes and high component commonality within product Bills of Materials. In particular, we conduct a series of simulation experiments to compare certain supply chain designs and investigate how their performance changes with changing variability of product configurations. The results indicate that under higher variability and component commonality conditions, a supply chain design that lays more emphasis on tracking the evolution of component demands and inventory positions performs better.

Feature modeling is a well-known approach to describe variability in Software Product Lines. Cardinality-based Feature Models (fms) is a type of fms where features can be instantiated several times in the configuration, contrarily to boolean fms where a feature is present or not. While boolean fms configuration is easily handled by current approaches, there is still a lack of support regarding cardinality-based fms. In particular, expressing constraints over the set of feature instances is not supported in current approaches, where cardinality involved in such constraints can not be specified. To face this limitation, we define in this paper cardinality-based expressions and provide the related formal syntax and semantics as well as the way to automate the underlying configuration. We study the need for such a support using cloud computing environment configurations as a motivating example. To evaluate the soundness of the proposed approach, we analyze a corpus of 10 cloud environments. Our empirical evaluation shows that constraints relying on our cardinality-based expressions are common and that our approach is effective and can provide an useful support to developers for modeling and reasoning about fms with cardinalities.

We propose a meta-meta framework architecture for supporting the behavior based integration of two business processes. The meta-meta level provides basic integration operators to the system administrator to create integration options for specific domains. Based on semantic relationships between nodes of two business processes these integration options are executed and transform parts of the business processes. The outcome of the model transformation is an integrated business process. The main advantage of this framework is the support of integration on multiple levels of varying domain independence as supported by the Model Driven Architecture.

DTU Orbit (19/08/2019) Modelling Product Families for Product Configuration Systems with Product Variant Master This article presents an evaluation of applying a suggested method for modelling product families for product configuration based on theory for modelling mechanical products,systems theory and object-oriented modelling. The modelling technique includes a so-called product variant master and CRC-cards for modelling and visualising the parts and properties of a complete product family. The modelling techniques include: Customer, engineering and part views on the product assortment to model the properties, functions and structure of the product family. This also makes it possible to map the links between the three views. Modelling of characteristics of the product variants in a product family Modelling of constraints between parts in the product family Visualisation of the entire product family on a poster e.g. 1x2 meters The product variant master and CRC-cards are means to ...

Russian agriculture has shown stable growth since 1999. The food trade balance steadily improves and the share of imported food in retail markets is decreasing due to the government's import substitution policies. Russia has re-emerged on the world arena as a food exporter and now ranks among the leading exporters of wheat and vegetable oil. Agricultural production growth has become export oriented. To continue its growth, Russia's agriculture should emphasize returning unused land to cultivation and adopt new technologies to increase the comparatively low crop and livestock yields. The skewed land distribution and agricultural support system, both strongly biased toward large farms and agroholdings, constrain the development of small farms and prevent their participation in food value chains, negatively impacting on rural development. 2.1. Steady growth driven by emphasis on profitable products Agriculture grew steadily since 1999, with Gross Agricultural Output (GAO) rising by nearly 55% between 1999 and 2017. This was a robust recovery after the collapse in the early 1990s when GAO dropped by 43% during the first decade of the transition 1990-1999 (Fig. 1). The long-term decline of the share of agriculture in GDP was reversed in recent years: it rose from 3.5% in 2012 to 4.4% in 2017, signifying that GAO grew faster than GDP. Agricultural labor productivity also grew faster than labor productivity in the economy as a whole (Fig. 2). 1 Agricultural growth was stimulated by the development of the private sector. The emergence of private agriculture after decades of collective and state farming was the outcome of Russia's agrarian reform

This paper is focused on modeling and optimization of spherical reactor configurations to produce dimethyl ether (DME) from methanol dehydration. A steady state heterogeneous one-dimensional mathematical model is developed based on the mass and energy conservation laws to predict the operability and performance of the proposed configurations. The spherical reactor is two concentric spheres that the space between spheres is filled by catalyst. To verify the accuracy of the considered model and assumptions, the simulation results of the conventional reactor are compared with the available plant data. The performance of the multi-stage spherical configurations is compared with the conventional industrial tubular reactor. In the optimization stage, DME production rate is maximized considering feasible decision variables using genetic algorithm as a powerful method in the global optimization. The simulation results show that increasing stages in the proposed spherical configuration enhances DME production capacity and decreases reactor diameter and thickness.

In mass customization, software configurators enable novice end-users to design customized products and services according to their needs and preferences. However, traditional configurators hardly provide an engaging experience while avoiding the burden of choice. We propose a Design Participation Model to facilitate navigating the design space, based on two modules. Modeler enables designers to create customizable designs as parametric models, and Navigator subsequently permits novice end-users to explore these designs. While most parametric designs support direct manipulation of low-level features, we propose interpolation features to give customers more flexibility. In this paper, we focus on the implementation of such interpolation features into Navigator and its user interface. To assess our approach, we designed and performed user experiments to test and compare Modeler and Navigator, thus providing insights for further developments of our approach. Our results suggest that ba...

Manufacturing companies widely use interactive configurators to specify product variants. These variants are created from different combinations of individual components. Constraints are usually imposed as relations between components to rule out invalid product configurations. The configurator and its underlying algorithm ensure the product specified by the user satisfies all constraints. We provide a method that models the online configurator as a series of highly parallelizable boolean satisfiability problems (SAT). Our methodology is facilitated by state-of-the-art tools such as the Microsoft Z3 theorem prover. Additionally, we confirm that the configurator problem is NP-complete. Hence, using SAT solving is not only natural but canonical. CCS CONCEPTS • Software and its engineering → Software prototyping; Software prototyping; • Theory of computation → Constraint and logic programming.

تقترح هذه المقالة رؤية منهاجية لتحقيق التكامل بين المسالك الجامعية للتربية بالمدارس العليا للأساتذة والتكوين الأساس لأطر هيئة التدريس بالمراكز الجهوية لمهن التربية والتكوين، وذلك بعد أن شخصت واقع التكوين بهاتين المؤسستين وكشفت عن العلاقة القائمة بينهما من خلال استقراء نصوصهما التنظيمية والإدارية وتحديد مهامهما وأدوارهما...
وقد اعتمدت هذه الرؤية التكاملية علىٰ ثلاثة مقومات، المقوم الأول: التكامل علىٰ مستوىٰ المهام والوظائف والأدوار، المقوم الثاني: التكامل علىٰ مستوىٰ مناهج وبرامج وصيغ التكوين في ضوء تكامل المهام المقترح، المقوم الثالث: التكامل علىٰ مستوىٰ إعداد البحوث التربوية والاستفادة من نتائجها.

This paper considers the modeling and control of a tubular fixed bed reactor with recycle stream for dimethyl ether (DME) production. For simulation purposes, a pseudo homogeneous model has been developed. By reactor simulation under steady state condition, effects of parameters such as feed rate, pressure and shell temperature are investigated. Using the steady state model, an optimizer that maximizes the reactor yield has been developed. For cooling the reactor, a steam drum that uses heat of reactions to produce steam was coupled with the reactor. Through dynamic simulation, system open loop response was obtained and two control loops were considered for controlling the reactor temperature and steam drum level. An optimizer that takes into account the feed variations was incorporated into the control system to maximize the DME production rate.

This textbook is about 'Production Planning and Scheduling'  (PPS)  in the Automotive Industry, which is the most interesting example for Mass Customization of  complex products and international supply chains. The theoretical fundament is the Ideal Boolean Algebra, which is a very new approach to master the planning and scheduling of customer configured products.
This new approach can be applied to other industries, which are on the way to configurable products with high complexity.

Clone-and-own is a common reuse practice that is widely adopted for evolving a family of software systems. However, this practice loses its effectiveness if not supported with valuable indicators that guide the derivation of new products. In this paper, we propose an approach to support the derivation of new product variants based on clone-and-own, by providing the possible scenarios in terms of operations to perform to accomplish the derivation. We generate a constraints system prior to a product derivation, to facilitate the software engineer selection of the suitable scenario and operations based on his preferences. In addition, we propose a cost estimation for each operation and respectively for each scenario, thus, a software engineer can rely on it as an additional parameter to achieve the derivation. The proposed scenarios and cost estimation are based on indicators retrieved after an automated identification of the mappings between the features implemented by the family of software products and the assets in which they are implemented. We preliminarily validate our approach on a case study where results show that the provided support can considerably reduce the amount of time and efforts that can be required to achieve a product derivation. Index Terms-Clone-and-own, product derivation, software reuse.

Many AI tasks, such as product configuration, decision support, and the construction of autonomous agents, involve a process of con-1 strained optimization, that is, optimization of behavior or choices subject to given constraints. In this paper we present an approach for constrained optimization based on a set of hard constraints and a preference ordering represented using a CP-network-a graphical model for representing qualitative preference information. This approach offers both pragmatic and computational advantages. First, it provides a convenient and intuitive tool for specifying the problem, and in particular, the decision maker's preferences. Second, it admits an algorithm for finding the most preferred feasible (Pareto optimal) outcomes that has the following anytime property: the set of preferred feasible outcomes are enumerated without backtracking. In particular, the first feasible solution generated by this algorithm is Pareto optimal.

We propose a directed graphical representation of utility functions, called UCP-networks, that combines aspects of two existing preference models: generalized additive models and CP-networks. The network decomposes a utility function into a number of additive factors, with the directionality of the arcs reflecting conditional dependence in the underlying (qualitative) preference ordering under a ceteris paribus interpretation. The CP-semantics ensures that computing optimization and dominance queries is very efficient. ...