Lean production system design for fishing net manufacturing using lean principles and simulation optimization

Value stream mapping (VSM) is a useful tool for describing the manufacturing state, especially for distinguishing between those activities that add value and those that do not. It can help in eliminating non-value activities and reducing the work in process (WIP) and thereby increase the service level. This research follows the guidelines for designing future state VSM. These guidelines consist of five factors which can be changed simply, without any investment. These five factors are (1) production unit; (2) pacemaker process; (3) number of batches; (4) production sequence; and (5) supermarket size. The five factors are applied to a fishing net manufacturing system. Using experimental design and a simulation optimizing tool, the five factors are optimized. The results show that the future state maps can increase service level and reduce WIP by at least 29.41% and 33.92% respectively. For the present study, the lean principles are innovatively adopted in solving a fishing net manufacturing system which is not a well-addressed problem in literature. In light of the promising empirical results, the proposed methodologies are also readily applicable to similar industries.     

Model repair — aligning process models to reality

Process mining techniques relate observed behavior (i.e., event logs) to modeled behavior (e.g., a BPMN model or a Petri net). Process models can be discovered from event logs and conformance checking techniques can be used to detect and diagnose differences between observed and modeled behavior. Existing process mining techniques can only uncover these differences, but the actual repair of the model is left to the user and is not supported. In this paper we investigate the problem of repairing a process model w.r.t. a log such that the resulting model can replay the log (i.e., conforms to it) and is as similar as possible to the original model. To solve the problem, we use an existing conformance checker that aligns the runs of the given process model to the traces in the log. Based on this information, we decompose the log into several sublogs of non-fitting subtraces. For each sublog, either a loop is discovered that can replay the sublog or a subprocess is derived that is then added to the original model at the appropriate location. The approach is implemented in the process mining toolkit ProM and has been validated on logs and models from several Dutch municipalities.     

Dreissenid veliger dynamics along a nearshore to offshore transect in Lake Michigan

Dreissenid mussel veligers compose a substantial component of pelagic biomass in the Great Lakes, yet their dynamics are poorly understood. To evaluate seasonal, spatial, and inter-annual variation in veliger density, we used a 64-μm mesh plankton net (2008, 2013–2016) and a 153-μm mesh plankton net (2007–2016) to collect dreissenid veligers at nearshore (15–25?m depth), transitional (45?m) and offshore (93–110?m) sites in southeast Lake Michigan during March–December. We also evaluated trends in density of recently settled mussels relative to veliger abundance and the density of the standing stock of adult mussels. Veliger density peaked during both summer and fall at all sites, but peak densities in summer were generally higher nearshore, whereas peak densities in the fall were generally higher offshore. The density of veligers in the 153-μm net was overall 28% of that in the 64-μm net, but there was high variability in this comparison among months. Smaller veligers were much more abundant in the 64-μm net, but there was little difference in the size distribution and abundance between nets for the 210–300?μm size classes. Thus, the 153-μm net could still be a useful tool for assessing density trends of larger veligers just prior to their settlement. Newly settled mussels (≤2?mm) were most abundant in summer or fall at the nearshore and offshore sites but were nearly absent at the transitional site despite the high density of veligers there. Factors other than veliger density must play an important role in mussel recruitment.     

Development of a safety critical software requirements verification method with combined CPN and PVS: a nuclear power plant protection system application

Safety-critical software systems such as certain nuclear instrumentation and control (NI&C) systems should be developed with thorough verification. This study presents a method of software requirement verification with a case study for a nuclear power plant (NPP) protection system. The verification introduces colored petri net (CPN) for system modeling and prototype verification system (PVS) for mathematical verification. In order to aid flow-through from modeling by CPN to mathematical proof by PVS, an information extractor from CPN models has been developed in this paper. In order to convert the extracted information to the PVS specification language, a translator has also been developed. This combined method has been applied to the functional requirements of the Wolsong NPP Shut Down System #2 (SDS2); logical properties of the requirements were verified. Through this research, guidelines and a tool support for the use of formal methods have been developed for application to NI&C software verification.     

理想收敛理论的非标准刻画

为了用非标准分析方法进一步研究拓扑空间，在扩大模型下，对理想收敛的基本理论进行了非标准刻画：设X是拓扑空间，I是X中的理想，I收敛于点x，当且仅当v(x)包含v(I)．给出了理想的极限点和聚点的非标准特征，利用极限点对闭包进行了非标准描述，并讨论了理想收敛与伴随网收敛的相互关系．     

Synchronization models for multimedia presentation with user participation

This paper addresses the key issue of providingflexible multimedia presentation with user participation and suggests synchronization models that can specify the user participation during the presentation. We study models like the Petrinet-based hypertext model and the object composition Petri nets (OCPN). We suggest adynamic timed Petri nets structure that can model pre-emptions and modifications to the temporal characteristics of the net. This structure can be adopted by the OCPN to facilitate modeling of multimedia synchronization characteristics with dynamic user participation. We show that the suggested enhancements for the dynamic timed Petri nets satisfy all the properties of the Petri net theory. We use the suggested enhancements to model typical scenarios in a multimedia presentation with user inputs.     

模糊Petri网及知识表示

在建造专家系统中虽然有很多种知识表示方法，但都有不尽人意的地方，本文试图用一种新的方法－Ｐｅｔｒｉ网模型来表示知识。本文给出了Ｆｕｚｚｚｙ Ｐｅｔｒｉ网和广义Ｆｕｚｚｙ Ｐｅｔｒｉ网两种模型，并给出了相应的推理算法，一旦专家知识用Ｐｅｔｒｉ网表示后，根据Ｐｅｔｒｉ网固有的特性，我们就能处理专家系统中并行推理、无回溯推理，反向推理等问题。     

Reliability models for computer systems: An overview including dataflow graphs

The reliability of a system is the probability that the system will perform its intended mission under given conditions. This paper provides an overview of the approaches to reliability modelling and identifies their strengths and weaknesses. The models discussed include structure models, simple stochastic models and decomposable stochastic models. Ignoring time-dependence, structure models give reliability as a function of the topological structure of the system. Simple stochastic models make direct use of the properties of underlying stochastic processes, while decomposable models consider more complex systems and analyse them through subsystems. Petri nets and dataflow graphs facilitate the analysis of complex systems by providing a convenient framework for reliability analysis.     

Petri net based scheduling

Timed Petri nets can be used to model and analyse scheduling problems. To support the modelling of scheduling problems, we provide a method to map tasks, resources and constraints onto a timed Petri net. By mapping scheduling problems onto Petri nets, we are able to use standard Petri net theory. In this paper we will show that we can use Petri net based tools and techniques to find conflicting and redundant precedences, upper- and lower-bounds for the makespan, etc. This is illustrated by a Petri net based analysis of the notorious 10×10 problem due to Fisher & Thompson (1963)     

Hierarchical intelligent control with flexible AC transmission systems application

A novel hierarchical intelligent controller configuration is proposed using an artificial neural network as a control-mode classifier in the supervisory level and a set of pre-designed controllers in the lower level. Controller outputs are modified nonlinearly by the classifying signals in a structure resembling one artificial neuron with adaptively changed weights. The lower-level local controllers are implemented using neural networks. An illustrative example of this approach is based on the transient stabilization of a single-machine infinite-bus system studied in Flexible AC Transmission Systems (FACTS) research.