Using Scrum to guide the execution of software process improvement in small organizations

For software process improvement - SPI - there are few small organizations using models that guide the management and deployment of their improvement initiatives. This is largely because a lot of these models do not consider the special characteristics of small businesses, nor the appropriate strategies for deploying an SPI initiative in this type of organization. It should also be noted that the models which direct improvement implementation for small settings do not present an explicit process with which to organize and guide the internal work of the employees involved in the implementation of the improvement opportunities. In this paper we propose a lightweight process, which takes into account appropriate strategies for this type of organization. Our proposal, known as a “Lightweight process to incorporate improvements”, uses the philosophy of the Scrum agile method, aiming to give detailed guidelines for supporting the management and performance of the incorporation of improvement opportunities within processes and their putting into practice in small companies. We have applied the proposed process in two small companies by means of the case study research method, and from the initial results, we have observed that it is indeed suitable for small businesses.     

Methodology for capturing and formalizing DFM Knowledge

Design for manufacturing (DFM) practices lead to more competitive products from the point of view of cost, development time and quality. However, the success of considering manufacturing issues during design process would be higher if manufacturing information was more readily available and designers needed less experience to select information relevant to DFM.     

Integration of product design,process planning,scheduling, and FMS control using XML data representation

An efficient model for communications between CAD, CAPP, and CAM applications in distributed manufacturing planning environment has been seen as key ingredient for CIM. Integration of design model with process and scheduling information in real-time is necessary in order to increase product quality, reduce the cost, and shorten the product manufacturing cycle. This paper describes an approach to integrate key product realization activities using neutral data representation. The representation is based on established standards for product data exchange and serves as a prototype implementation of these standards. The product and process models are based on object-oriented representation of geometry, features, and resulting manufacturing processes. Relationships between objects are explicitly represented in the model (for example, feature precedence relations, process sequences, etc.). The product model is developed using XML-based representation for product data required for process planning and the process model also uses XML representation of data required for scheduling and FMS control. The procedures for writing and parsing XML representations have been developed in object-oriented approach, in such a way that each object from object-oriented model is responsible for storing its own data into XML format. Similar approach is adopted for reading and parsing of the XML model. Parsing is performed by a stack of XML handlers, each corresponding to a particular object in XML hierarchical model. This approach allows for very flexible representation, in such a way that only a portion of the model (for example, only feature data, or only the part of process plan for a single machine) may be stored and successfully parsed into another application. This is very useful approach for direct distributed applications, in which data are passed in the form of XML streams to allow real-time on-line communication. The feasibility of the proposed model is verified in a couple of scenarios for distributed manufacturing planning that involves feature mapping from CAD file, process selection for several part designs integrated with scheduling and simulation of the FMS model using alternative routings.     

Pattern recognition of manufacturing process signals using Gaussian mixture models-based recognition systems

Unnatural patterns exhibited in manufacturing processes can be associated with certain assignable causes for process variation. Hence, accurate identification of various process patterns (PPs) can significantly narrow down the scope of possible causes that must be investigated, and speed up the troubleshooting process. This paper proposes a Gaussian mixture models (GMM)-based PP recognition (PPR) model, which employs a collection of several GMMs trained for PPR. By using statistical features and wavelet energy features as the input features, the proposed PPR model provides more simple training procedure and better generalization performance than using single recognizer, and hence is easier to be used by quality engineers and operators. Furthermore, the proposed model is capable of adapting novel PPs through using a dynamic modeling scheme. The simulation results indicate that the GMM-based PPR model shows good detection and recognition of current PPs and adapts further novel PPs effectively. Analysis from this study provides guidelines in developing GMM – based SPC recognition systems.     

Method for analysis and dynamism of factory structure in automotive manufacturing

A turbulent environment characterized by unsteady economic cycles, customized products, a growing bandwidth of products, an exploding number of variants and shorter product life cycles force manufacturers to permanent adaptation of their factories. Flexible and changeable structures will be required to enable factories dealing with the technological challenges and economic pressure of the future competitively. In order to achieve changeability objectives in manufacturing, a detailed analysis of existing structures and its representative attributes is essential. It is the basis for systematic structure planning of factories. In this paper a method for analyzing the capacitive and technological structure of a factory embedded in a network of manufacturing and its network of suppliers is presented. The synchronization of product and production development under the influence of change is intended. Therefore, the structural views of product and production are specifically in focus of the method. Based on the results of the analysis models an approach of a tool for giving product and production structure dynamism is suggested to investigate the effects and dependencies of change drivers in manufacturing.     

Identifying some important success factors in adopting agile software development practices

Agile software development (ASD) is an emerging approach in software engineering, initially advocated by a group of 17 software professionals who practice a set of “lightweight” methods, and share a common set of values of software development. In this paper, we advance the state-of-the-art of the research in this area by conducting a survey-based ex-post-facto study for identifying factors from the perspective of the ASD practitioners that will influence the success of projects that adopt ASD practices. In this paper, we describe a hypothetical success factors framework we developed to address our research question, the hypotheses we conjectured, the research methodology, the data analysis techniques we used to validate the hypotheses, and the results we obtained from data analysis. The study was conducted using an unprecedentedly large-scale survey-based methodology, consisting of respondents who practice ASD and who had experience practicing plan-driven software development in the past. The study indicates that nine of the 14 hypothesized factors have statistically significant relationship with “Success”. The important success factors that were found are: customer satisfaction, customer collaboration, customer commitment, decision time, corporate culture, control, personal characteristics, societal culture, and training and learning.     

Acceptance of agile methodologies: A critical review and conceptual framework

It is widely believed that systems development methodologies (SDMs) can help improve the software development process. Nevertheless, their deployment often encounters resistance from systems developers. Agile methodologies, the latest batch of SDMs that are most suitable in dealing with volatile business requirements, are likely to face the same challenge as they require developers to drastically change their work habits and acquire new skills. This paper addresses what can be done to overcome the challenge to agile methodologies acceptance. We provide a critical review of the extant literature on the acceptance of traditional SDMs and agile methodologies, and develop a conceptual framework for agile methodologies acceptance based on a knowledge management perspective. This framework can provide guidance for future research into acceptance of agile methodologies, and has implications for practitioners concerned with the effective deployment of agile methodologies.     

电子装配行业的MES体系结构及技术实现

针对电子装配行业的特点和制造执行系统（MES）的需求,采用基于SOA的设计方法和理念,提出基于Web服务的MES软件体系结构,建立基于工作流的电子装配过程实时可视化、实时生产排程、实时生产过程跟踪技术框架。提出基于WebServices技术和J2EE平台的软件体系结构技术实现框架。开发的MES系统应用在某SMT车间,证明该系统具有较好的实时、可配置、可重构、可集成性能。     

Application of fuzzy sets to manufacturing/distribution planning decisions in supply chains

In the real-world manufacturing/distribution planning decision (MDPD) integration problems in supply chains, the environmental coefficients and parameters are normally imprecise due to incomplete and/or unavailable information. This work presents a fuzzy linear programming approach based on the possibility theory. It applies this approach to solve multi-product and multi-time period MDPD problems with imprecise goals and forecast demand by considering the time value of money of related operating cost categories. The proposed approach attempts to minimize the total manufacturing and distribution costs by considering the levels of inventory, subcontracting and backordering, the available machine capacity and labor levels at each source, forecast demand and available warehouse space at each destination. This study utilizes an industrial case study to demonstrate the feasibility of applying the proposed approach to practical MDPD problems. The primary contribution of this paper is a fuzzy mathematical programming methodology for solving the MDPD integration problems in uncertain environments.