Modeling production configuration using nested colored object-oriented Petri-nets with changeable structures

Configuring production processes based on process platforms has been well recognized as an effective means for companies to provide product variety while maintaining mass production efficiency. The production processes of product families involve diverse variations in manufacturing and assembly processes resulted from a large variety of component parts and assemblies. This paper develops a multilevel system of nested colored object-oriented Petri nets with changeable structures to model the configuration of production processes. To capture the semantics associated with production configuration decisions, some unique modeling mechanisms are employed, including colored Petri nets, object-oriented Petri nets, changeable Petri net structures, and net nesting. The modeling formalism comprises resource nets, manufacturing nets, assembly nets and process nets. The paper demonstrates how these net definitions are applied to the specification of production process variants at different levels of abstraction. Also reported is a case study in an electronics company. The system model is further analyzed with focus on conflict prevention and deadlock detection

PROCESS PLATFORM FORMATION FOR PRODUCT FAMILIES

ABSTRACT In accordance with the product families, process platforms have been recognized as a promising tool for companies to configure optimal, yet similar, production processes for producing different products. This paper tackles process platform formation from large volumes of production data available in companies' production systems. A data mining methodology based on text mining and tree matching is developed for the formation of process platforms. A case study of high variety production of vibration motors for mobile phones is reported to prove the feasibility and potential of forming process platforms using text mining and tree matching

Process platform-based production configuration for mass customization

A critical issue facing today’s manufacturing companies is to achieve product proliferation while maintaining an economy of scale in production. The consequence of high product variety manifests itself through an exponentially increased number of process variations, which introduces significant constraints to production planning and control and prevents make-to-order systems from building up customization capabilities. Managing product differentiation based on product and process families sharing common platforms has been well recognized as an effective means to deal with such a variety dilemma in many industries. This research proposes systematic methodologies of process platform-based production configuration. The principle is to support production planning in configuring existing operations and processes by exploiting similarity and repetitions inherent in product and process families.DOCTOR OF PHILOSOPHY (MAE

A high-resolution single-molecule sequencing-based Arabidopsis transcriptome using novel methods of Iso-seq analysis

Background: Accurate and comprehensive annotation of transcript sequences is essential for transcript quantification and differential gene and transcript expression analysis. Single-molecule long-read sequencing technologies provide improved integrity of transcript structures including alternative splicing, and transcription start and polyadenylation sites. However, accuracy is significantly affected by sequencing errors, mRNA degradation, or incomplete cDNA synthesis. Results: We present a new and comprehensive Arabidopsis thaliana Reference Transcript Dataset 3 (AtRTD3). AtRTD3 contains over 169,000 transcripts—twice that of the best current Arabidopsis transcriptome and including over 1500 novel genes. Seventy-eight percent of transcripts are from Iso-seq with accurately defined splice junctions and transcription start and end sites. We develop novel methods to determine splice junctions and transcription start and end sites accurately. Mismatch profiles around splice junctions provide a powerful feature to distinguish correct splice junctions and remove false splice junctions. Stratified approaches identify high-confidence transcription start and end sites and remove fragmentary transcripts due to degradation. AtRTD3 is a major improvement over existing transcriptomes as demonstrated by analysis of an Arabidopsis cold response RNA-seq time-series. AtRTD3 provides higher resolution of transcript expression profiling and identifies cold-induced differential transcription start and polyadenylation site usage. Conclusions: AtRTD3 is the most comprehensive Arabidopsis transcriptome currently. It improves the precision of differential gene and transcript expression, differential alternative splicing, and transcription start/end site usage analysis from RNA-seq data. The novel methods for identifying accurate splice junctions and transcription start/end sites are widely applicable and will improve single-molecule sequencing analysis from any species