Formal Modeling Methodology Research Articles

Optimal selection and investment-allocation decisions for sustainable supplier development practices

Organization’s sustainability performance is influenced by its suppliers’ sustainability performance. This relationship makes sustainable supplier development a strategic competitive option for a buyer or focal organization. When considering sustainable supplier development practices (SSDPs) adoption, organizations have to balance and consider their limited financial resources and operational constraints. It becomes necessary to both select the best SSDPs set and investment allocation among the selected SSDP set such that the organization can maximize overall sustainability performance level. In this paper, an integrated formal modeling methodology using DEMATEL, the NK model, and multi-objective linear programming model is used support this objective. The proposed methodology is evaluated in a practical sustainable supply chain field study of an equipment manufacturing company in China. Through case study, we found that the interdependency among SSDPs must be considered in SSDPs selection and investment allocation problem. Theoretical, managerial and methodology implications, conclusions, and directions for future research are also presented.

How Does the Modeling Strategy Influence Design Optimization and the Automatic Generation of Parametric Geometry Variations?

The robustness and flexibility of a feature-based parametric CAD model determines the extent to which the geometry can be modified and reused in other design scenarios. The ability of a model to successfully adapt to changes depends on the type and sequence of the modeling operations selected to build the geometry, the parent–child dependencies defined during the modeling process, and the type and scope of the desired geometric change. Several formal modeling methodologies have been proposed to maximize model reusability, which have been shown to outperform unstructured approaches when designers need to manually modify the geometry. However, the effect of these parametric model strategies on the generation of valid solutions in heavily automated tasks has not yet been investigated. In this paper, we compare and analyze the performance of three well-established parametric modeling methodologies in various design optimization scenarios that involve the automatic generation of a large number of geometric variations. We discuss the results of a study with four parametric models of varying complexity and identify the limitations of each strategy in relation to the internal structure of the model. Our results show that explicit references and resilient modeling strategies are relatively robust for simple parts, but their effectiveness decreases significantly as the complexity of the model increases. In addition, we introduce the concept of intrinsic variability, which impacts the effectiveness of the methodology, and thus the quality of the parametric model, based on how the methodology is interpreted and executed. • The effect of formal parametric model strategies on the automatic generation of geometric variations is investigated. • A study with three formal methodologies and four parametric feature-based models of varying complexity is presented. • The horizontal modeling methodology is not an efficient strategy for automated environments. • The resilient methodology is most effective for simple parts and scenarios that involve manual changes. • Explicit reference modeling is effective for complex models and yields faster model regeneration times.

A dynamical model of an aeration plant for wastewater treatment using a phenomenological based semi-physical modeling methodology

Diffused aeration is a sensitive process for wastewater treatment. Because of the nonlinearity and complexity of aerator dynamics due to microorganism metabolism and oxygen transfer, reliable mathematical models are needed to perform control-oriented tasks. To this end, in this study we develop a phenomenological based semi-physical model (PBSM) to predict and describe the dynamic behavior of the oxygen transfer in a diffused aeration process by means of a formal modeling methodology. This model will then be validated by using data from an aeration pilot plant. In this paper, we also show a lack of agreement in the literature in terms of the different available ways to represent the volumetric oxygen transfer coefficient kLa. Reasonable agreement between the developed model and plant data is found by considering a phenomenological approach of the kLa instead of considering many of the available empirical correlations in the literature.

Formal modeling of biomedical signal acquisition systems: source of evidence for certification

Biomedical signal acquisition systems are software-intensive medical systems composed of processors, transducers, amplifiers, filters, and converters. We present in this article a formal modeling methodology of biomedical signal acquisition systems using Colored Petri Nets (CPN) and based on a frequency-domain approach. In the methodology, a reference model represents the main features of these medium risk systems. We argue that this kind of model is useful to assist manufacturers to reduce the number of defects in systems and to generate safety and effectiveness evidence throughout certification. Therefore, we describe two main contributions in this article. We provide a reference model of biomedical signal acquisition systems and show how manufacturers can generate evidence by means of an electrocardiography (ECG) case study. We carried out the case study by extending the reference model to represent the behavior of an ECG system using a basic cardiac monitor configuration based on the single-lead, heart rate monitor front end (AD8232) and the low power precision analog microcontroller, ARM cortex M3 with dual sigma-delta converters (ADUCM360). We verified the model against safety requirements with the model checking technique (safety evidence) and validated it by comparing output signals with a filtered ECG record available on the PHYSIONET ECG-ID database in the frequency and time domains (effectiveness evidence). This methodology enables manufacturers to identify defects in systems earlier in the development process aiming to decrease costs and development time.

Parametric CAD modeling: An analysis of strategies for design reusability

CAD model quality in parametric design scenarios largely determines the level of flexibility and adaptability of a 3D model (how easy it is to alter the geometry) as well as its reusability (the ability to use existing geometry in other contexts and applications). In the context of mechanical CAD systems, the nature of the feature-based parametric modeling paradigm, which is based on parent–child interdependencies between features, allows a wide selection of approaches for creating a specific model. Despite the virtually unlimited range of possible strategies for modeling a part, only a small number of them can guarantee an appropriate internal structure which results in a truly reusable CAD model. In this paper, we present an analysis of formal CAD modeling strategies and best practices for history-based parametric design: Delphi’s horizontal modeling, explicit reference modeling, and resilient modeling. Aspects considered in our study include the rationale to avoid the creation of unnecessary feature interdependencies, the sequence and selection criteria for those features, and the effects of parent/child relations on model alteration. We provide a comparative evaluation of these strategies in the form of a series of experiments using three industrial CAD models with different levels of complexity. We analyze the internal structure of the models and compare their robustness and flexibility when the geometry is modified. The results reveal significant advantages of formal modeling methodologies, particularly resilient techniques, over non-structured approaches as well as the unexpected problems of the horizontal strategy in numerous modeling situations.

어포던스 기반의 인간-기계 협업 모델을 이용한 제조 시스템 구현 연구

Yeong Gwang Oh․Ikchan Ju․Wooyeol Lee․Namhun KimThe Department of Human and Systems Engineering, UNIST(Ulsan National Institute of Science and Technology) Modeling and control of human-involved manufacturing systems poses a huge challenge on how to model all possible interactions among system components within the time and space dimensions. As the manufacturing environment are getting complicated, the importance of human in the manufacturing system is getting more and more spotlighted to incorporate the manufacturing flexibility. This paper presents a formal modeling methodo-logy of affordance-based MPSG (Message-based Part State Graph) for a human-machine collaboration system incorporating supervisory control scheme for flexible manufacturing systems in automotive industry. Basically, we intend to extend the existing model of affordance-based MPSG to the real industrial application of human- machine cooperative environments. The suggested extension with the real industrial example is illustrated in three steps; first, the manufacturing process and relevant data are analyzed in perspectives of MABA-MABA and the supervisory control; second, the manufacturing processes and task allocation between human and machine are mapped onto the concept of MABA-MABA; and the last, the affordance-based MPSG of human- machine collaboration for the manufacturing process is presented with UMLs for verification.

1A1-U03 協調作業ロボットシステムのための自律分散型コントローラの設計と実装(生産システム・生産機器メカトロニクス)

This paper describes a systematic method for design and implementation of distributed autonomous controllers in cooperative multi-robot systems. Based on our previous concepts of non-centralized grouping robots, and bionic self-reproducing, self-assembling, and self-organizing molecular mobile robots, a totally distributed coordination algorithm is developed to provide robustness to multi-robot manufacturing and assembly missions using Petri net based formal modeling methodologies. In a bionic assembly factory environment, where a number of autonomous mobile robots function with own controller and inter-robot communication facilities, each robot plans the subtasks sequence, decides the workstation for the next assembly step with general knowledge of the plant layout, and at the station performs the assembly subtask autonomously or cooperatively with other robots, avoiding resource competition and sharing operation experience. Embedded Petri net models of autonomous task execution and implementation issues are presented for a prototyping experimental system.

The Formal Design Models of a Set of Abstract Data Types (ADTs)

Type theories are fundamental for underpinning data object modeling and system architectural design in computing and software engineering. Abstract Data Types (ADTs) are a set of highly generic and rigorously modeled data structures in type theory. ADTs also play a key role in Object-Oriented (OO) technologies for software system design and implementation. This paper presents a formal modeling methodology for ADTs using the Real-Time Process Algebra (RTPA), which allows both architectural and behavioral models of ADTs and complex data objects. Formal architectures, static behaviors, and dynamic behaviors of a set of ADTs are comparatively studied. The architectural models of the ADTs are created using RTPA architectural modeling methodologies known as the Unified Data Models (UDMs). The static behaviors of the ADTs are specified and refined by a set of Unified Process Models (UPMs) of RTPA. The dynamic behaviors of the ADTs are modeled by process dispatching technologies of RTPA. This work has been applied in a number of real-time and non-real-time system designs such as a Real-Time Operating System (RTOS+), a Cognitive Learning Engine (CLE), and the automatic code generator based on RTPA.

Formal modeling methodologies for control of manufacturing cells: Survey and comparison

Over the last two decades, several formal modeling methodologies have emerged. In the manufacturing cell control domain, these methodologies are directed toward integrating the requirements specification, the design, and the implementation of the cell controller into a consistent process, supported by efficient analysis and development tools. The search for a single methodology powerful enough to span all the stages of the development life cycle of a formal model capable of replacing existing non-formal practices, however, has proven more difficult than expected. This paper presents a survey of several formal modeling methodologies that have been used for manufacturing cell control. Furthermore, the methodologies are classified and compared based on their expressive power, their verification power, their level of abstraction, and their span in relation to the formal model's development life cycle.

Formal modeling methodologies for control of manufacturing cells: Survey and comparison : Ignacio Castillo, Jeffrey S. Smith, v21, n1, 2002, pp40–57

The invaluable health, economic and social impacts of vaccination are hard to exaggerate. The ability to stabilize vaccines is urgently required for their equitable distribution without the dependence on the ‘cold-chain’ logistics. Herein, for the first time we report biomimetic-mineralization of live-viral vaccines using metal-organic frameworks (MOFs) to enhance their storage stability from days to months. Applying ZIF-8 and aluminium fumarate (Alfum), the Newcastle Disease Virus (NDV) V4 strain and Influenza A WSN strain were encapsulated with remarkable retention of their viral titre. The [email protected], [email protected] and [email protected] composites were validated for live-virus recovery using a tissue culture infectious dose (TCID50) assay. With the objective of long-term stabilization, we developed a novel, trehalose (T) and skim milk (SM) stabilized, freeze-dried [email protected] composite, [email protected]+T/SM. The thermal stability of this composite was investigated and compared with the control NDV and non-encapsulated, freeze-dried NDV+T/SM composite at 4 °C, RT, and 37 °C over a period of 12 weeks. We demonstrate the fragility of the control NDV vaccine which lost all viability at RT and 37°C by 12 and 4 weeks, respectively. Comparing the freeze-dried counterparts, the MOF encapsulated [email protected]+T/SM demonstrated significant enhancement in stability of the NDV+T/SM composite especially at RT and 37 °C upto 12 weeks.Vaccination is undoubtedly one of the most effective medical interventions, saving millions of lives each year. However, the requirement of ‘cold-chain’ logistics is a major impediment to widespread immunization. Live viral vaccines (LVVs) are widely used vaccine types with proven efficacy and low cost. Nonetheless, their complex composition increases their susceptability to thermal stress. Several LVV thermostabilization approaches have been investigated, including their complex engineering and the facile addition of stabilizers. Still, the lack of a universal approach urgently requires finding a stabilization technique especially when additives alone may not be sufficient. Herein, we demonstrate MOF biomimetic-mineralization technology to encapsulate LVVs developing an optimised composite which significantly preserves vaccines without refrigeration for extended periods of time.