A development framework for supervisory control software of automated manufacturing systems

In order to solve the problem that it is difficult to achieve better multi-robot coordination operation using the original control system in multi-robot cooperative systems, this paper conducts system modeling, control framework design and software development and verification experiments for multi-robot cooperative systems. We firstly model the system composed of multiple robots and operated objects. The coordination between any two robots can be divided into two categories: loose coordination and tight coordination according to the constraint relationship between the robots and the objects, based on which the kinematics and dynamics analysis of the multi-robot system is carried out. A multi-robot cooperative control framework is designed, which contains modules for task planning, force and position assignment, sensor information acquisition, position/force control and synchronization clock. On the basis of the multi-robot cooperative control system, the robot cooperative control software is designed and developed, and the software system contains, with excellent characteristics. Finally, an experimental environment containing three large-load EFORT industrial robots was established and experiments were conducted using the developed multi-robot cooperative control software to verify the usability and reliability of the software system.

A three-step approach is proposed to substantially reduce the high cost of development of control software for an FMS on the shop floor. First, by introducing the concept of multiple computing processes into Automata Theory, a finite capacity machine (FCM) is presented as an extended finite machine. An FCM is used to model the control of a flexible manufacturing system, which avoids the state explosion problem. Secondly, a structured adaptive supervisory control (SASC) model meeting the desired control objectives for an FMS is derived from a composed FCM. The SASC model can be constructed systematically. Finally, generic software components for an SASC model are described, which allow the SASC model to be cost-effectively transferred into shop-floor applicable control software.

Many papers proposed in the software engineering and information systems literature are dedicated to analysis of software projects missing their schedules, exceeding their budgets, delivering software products with poor quality and in some cases even wrong functionality. The expression “software crisis“ has been coined since the late 60's to illustrate this phenomenon. Various solutions has been proposed by academics and practitioners in order to deal with the software crisis, counter these trends and improve productivity and software quality. Such solutions recommend software process improvement as the best way to build software products needed by modern organizations. Among the well-known solutions, many are based either on software development tools or on software development approaches, methods, processes, and notations. Nevertheless, the scope of these solutions seems to be limited and the improvements they provide are often not significant. We think that since software artifacts are accumulation of knowledge owned by organizational stakeholders, the software crisis is due to a knowledge gap resulting from the discrepancy between the knowledge integrated in software systems and the knowledge owned by organizational actors. In particular, integrating knowledge management in software development process permits reducing the knowledge gap through building software products which reflect at least partly the organization's know-how. In this paper, we propose a framework which provides a definition of knowledge based on information systems architecture and describes a knowledge-oriented software development process to help organizations in reducing the software crisis impacts.

The automation of manufacturing systems is one of the most important aspects that need to be taken care of during a design process. The Product Lifecycle Management (PLM) tools allow for the designing of automated systems even before acquiring all the hardware and/or software. This paper shows the use of this PLM kind of tools for mixing virtual and real components on an automated manufacturing system through the implementation of four different case scenarios: using the real process/real controller to the virtual process/virtual controller, real process/real controller to real process/virtual controller and finally, virtual process/real controller to virtual process/virtual controller. These scenarios will be described along with their purposes and the tools used to achieve them. Dassault Systemes DELMIA Automation is used as a PLM tool and is combined with the hardware and software required to achieve each case scenario. The case study used is the Flexible Manufacturing System in the Mechatronics laboratory at the Tecnologico de Monterrey; it’s also presented an implementation of these scenarios in a Manufacturing Systems Automation laboratory class. This study examines students’ use of technology for learning compared to more traditional learning methods. Results suggest that there is more than one good way to learn.

Software metrics are measures of software. Their primary use is to help us plan and predict software development. We can better control software quality and development effort if we can quantify the software. This is especially true in the early stages of development. Research has been done in the area of predicting software maintenance effort from software metrics. In general, software metrics can be classified into two categories: software product metrics and software process metrics. Software product metrics are measures of software products such as source code and design documents. Software process metrics are measures of software development process. For example, the size of the software is a measure of the software product itself, thus a product metrics. The effort required to design a software system may be influenced by how the software is designed, thus a process metrics. In this article, only software product metrics are addressed.

Welcome to the International Conference on Software and Systems Process (ICSSP) held in Zurich, Switzerland, on June 2nd and 3rd, 2012. Having grown from a Software Process Workshop in 2005 to the International Conference on Software Process (ICSP) in 2007, and finally to the International Conference on Software and Systems Process (ICSSP) in 2011, this conference series has established its place in the software engineering community as a respected conference focusing on research and practice related to software and systems development process. Software and software systems development use processes as one major means for achieving and ensuring the quality of the final product. This leads to specific challenges regarding software processes such as simplicity, adaptability, standard conformance, the coordination of multiple domains and lifecycles, etc. Processes from other domains (e.g., health care, manufacturing, business, aerospace, automotive systems, and others) face similar challenges. Yet, they share interesting similarities with and differences to software processes. The question is: How can we in the software domain learn from other domains to meet our software process engineering challenges? The ICSSP conferences hence connect the traditional software and systems process community with outside views and insights, broadening its scope of software development processes to system development and explicitly including processes of other domains such as health care, business, and manufacturing. By sharing process development theories and practices from such domains, ICSSP 2012 is investigating novel solutions to today's process challenges. Correspondingly, the main theme of ICSSP 2012 is Beyond Software and Software Systems Processes, signaling our goal of learning from domains other than the traditional software process community.

This scientific article presents the results of a study focused on the current practices and future prospects of AI-tools usage, specifically large language models (LLMs), in software development (SD) processes within European IT companies. The Pan-European study covers 35 SD teams from all regions of Europe and consists of three sections: the first section explores the current adoption of AI-tools in software production, the second section addresses common challenges in LLMs implementation, and the third section provides a forecast of the tech future in AI-tools development for SD. The study reveals that AI-tools, particularly LLMs, have gained popularity and approbation in European IT companies for tasks related to software design and construction, coding, and software documentation. However, their usage for business and system analysis remains limited. Nevertheless, challenges such as resource constraints and organizational resistance are evident. The article also highlights the potential of AI-tools in the software development process, such as automating routine operations, speeding up work processes, and enhancing software product excellence. Moreover, the research examines the transformation of IT paradigms driven by AI-tools, leading to changes in the skill sets of software developers. Although the impact of LLMs on the software development industry is perceived as modest, experts anticipate significant changes in the next 10 years, including AI-tools integration into advanced IDEs, software project management systems, and product management tools. Ethical concerns about data ownership, information security and legal aspects of AI-tools usage are also discussed, with experts emphasizing the need for legal formalization and regulation in the AI domain. Overall, the study highlights the growing importance and potential of AI-tools in software development, as well as the need for careful consideration of challenges and ethical implications to fully leverage their benefits.

In particular, an early integration of performance specifications in the SDP has been recognized during the last few years as an effective approach to improve the overall quality of a software. Performance related problems are becoming more and more strategic in the software development, especially recently with the advent of Web Services and related business-oriented composition techniques (software as a service, Web 2.0, orchestration, choreography, etc.). The goal of our work is the definition of a software development process that integrates performance evaluation and prediction. The software performance engineering development process (SPEDP) we specify is focused on performance, which plays a key role driving the software development process, thus implementing a performance/QoS-driven (software) development process. More specifically, in this paper our aim is to formally define the SPEDP design process, posing particular interest on the basis, on the first step of SPEDP, the software/system architecture design, modeling and/or representation. We define both the diagrams to use and show how to model the structure of the software architecture, its behavior and performance requirements. This is the first mandatory step for the automation of the SPEDP into a specific tool.

Nowadays due to the technology development and use of digital computers in various systems, need for development of high performance and robust software is attracting great attentions. Because of increasing complexity in algorithms and implementation hardware for embedded systems, proper simulation tools are required. In sophisticated systems design, hardware in the loop (HIL) simulation is known as a prominent simulation tool before realistic tests of the system and a step after software simulation. Simultaneously it can be used for verification and validation of automation and control software. HIL has had an historical background in aerospace industries. Recently, this tool has spread in different steps of system life cycle such as design, development, implementation and test of various applications including automobile industry, shipbuilding, power lines, robotic systems and etc. Utilizing a suitable hardware in the loop laboratory, in system design stages is a practical way to increase the system reliability and efficiency as well as value of product. Also, by proper investigation in this modelling and simulation method, many errors can be avoided in design procedure of software and hardware as well as their interconnections. In this study, structure and components of an hardware in the loop laboratory for different systems are explored, also it is tried to more evaluate the applications of HIL simulations in dynamics and control engineering. At last, general structure of an hardware in the loop lab for diverse industries is proposed and discussed.

The low-code approach is an important area of research being developed to improve the rapid creation and performance of software applications. This approach allows developers and users to easily create software applications through an interactive interface. Existing research shows that the low-code approach accelerates the development process in innovative ways, saves effort and time, and reduces code complexity. This study analyses and compares automatic code generation and transformation techniques in low-code platforms. The study analyses the contributions of automatic code generation and transformation to software engineering processes and evaluates the impact of these techniques on software product quality and development speed. The importance of the Model-Based Development (MBD) approach in automated code generation processes is highlighted. It is stated that MBD provides benefits such as speeding up the software development process and reducing errors by enabling automatic code generation from high-level abstract models. In the study, various literature studies were evaluated to examine the impact of automatic code generation and transformation techniques on the application development process. These studies have shown how automatic code generation and transformation techniques are applied, what results are achieved and what contributions these techniques make to the software development process. The results of the study show that automatic code generation and transformation techniques have a great impact on the application development process. In particular, the acceleration of the software development process, the reduction of errors and the ability to produce more effective and efficient software products are important benefits of these techniques. In addition, it has been found that this approach increases the success of software projects by enabling software developers to produce fast and accurate solutions in complex systems. In this context, the importance of automatic code generation and transformation techniques plays an important role in software development processes.

The software development process (SDP) contains many variables depending on the methodology chosen. Software development methodologies such as Agile or Waterfall can specify how and in what sequence software is developed. However, the SDP remains a hot topic among practitioners and academics, who seek to clarify the key aspects that influence the successful implementation of the SDP. As the SDP is a dynamic and knowledge-intensive business process (BP), one of its most impact components is the human factor (HF). It is difficult to predict how the HF impacts the sequence and results of SDP implementation. This paper proposes a new approach to investigate the impact of the HF on the SDP through the perspectives of different software development methodologies. The advantages and novelties of this approach include modelling HF uncertainties through their fuzzification in SDP activities, modelling different SDP methodologies using a case-handling approach, and simulating a dynamic, case-based SDP with real HF-related data collected from several IT organizations. The results show that the impact of the HF on SDP performance differs across the Waterfall and Agile methodologies. The results also allow researchers and practitioners working on software development projects to familiarize themselves with the impact of the HF on different SDPs, and to assess the degree of development risk associated with the SDP depending on the methodology chosen.

Performance related problems are becoming more and more strategic in the software development, especially recently with the advent of Web Services and related business-oriented composition techniques (software as a service, Web 2.0, orchestration, choreography, etc.). In particular, an early integration of performance specifications in the SDP has been recognized during the last few years as an effective approach to improve the overall quality of a software. The goal of our work is the definition of a software development process that integrates performance evaluation and prediction. The software performance engineering development process (SPEDP) we specify is focused on performance, which plays a key role driving the software development process, thus implementing a performance/QoS-driven (software) development process. More specifically, in this paper our aim is to formally define the SPEDP design process, posing particular interest on the basis, on the first step of SPEDP, the software/system architecture design, modeling and/or representation. We define both the diagrams to use and show how to model the structure of the software architecture, its behavior and performance requirements. This is the first mandatory step for the automation of the SPEDP into a specific tool, which we have partially implemented as a performance plug-in for ArgoUML, ArgoPerformance.

Many companies in the automotive industry have adopted model-driven development in their vehicle software development. As a major automotive company, General Motors (GM) has been using a custom-built, domain-specific modeling language, implemented as an internal proprietary metamodel, to meet the modeling needs in its control software development. Since AUTomotive Open System ARchitecture (AUTOSAR) has been developed as a standard to ease the process of integrating components provided by different suppliers and manufacturers, there has been a growing demand to migrate these GM-specific, legacy models to AUTOSAR models. Given that AUTOSAR defines its own metamodel for various system artifacts in automotive software development, we explore applying model transformations to address the challenges in migrating GM-specific, legacy models to their AUTOSAR equivalents. As a case study, we have built and validated a model transformation using the MDWorkbench tool, the Atlas Transformation Language, and the Metamodel Coverage Checker tool. This paper reports on the case study, makes observations based on our experience to assist in the development of similar types of transformations, and provides recommendations for further research.

Empirical investigations clearly show that in contrast to the theory which implies that the use of methods in software development is beneficial, their use in practice is actually very low. Several reasons have been identified recently as contributing to this rather paradoxical situation. Most importantly: the socio-technical inappropriateness of a prescribed method to the company's actual ways of working, and the rigidity, i.e. inability of a prescribed method to be adapted to a particular problem. In this paper, we present a framework that deals with these issues. Its purpose is to help software development companies to reengineer their software development processes by establishing formalized and flexible methods based on the actual ways of working in that companies. The framework has been developed in cooperation with software development companies.

Diagnostic Emulation is the application of microprogramming to the emulation of an operational computer to support software development and verification for that computer. A conventional technique, Interpretive Computer Simulation (ICS), has been used for many years in support of such software development and verification efforts. The ICS method is becoming less cost effective. For the development of attitude control software for NASA's High Energy Astronomical Observatory (HEAO) diagnostic emulation was considered as an alternative. This paper describes the motivation for using an ICS or diagnostic emulator to validate command and control software, the potential advantages of microprogramming, and the analysis which led to the development of the HEAO Diagnostic Emulator rather than the use of conventional techniques. Also discussed are the emulator implementation tradeoff analysis, the resulting program design, and the interface between the microprogram and the assembly language modules. The results to date are described, including the capability, speed, and reliability of the program and initial user response.