Product delivering companies invest resources in product development activities in order to create value. Still, when performance in product development is to be evaluated, time, cost, and quality are in focus, especially in the later stages of the development when it is expensive and difficult to make any changes. Time, cost, and quality are important dimensions of performance but they are not revealing the complete picture. Missing is the value perspective. This paper outlines a method for how perceived customer value can be used to evaluate performance in product development and describes how it is verified through a case study. By using the perceived customer value of requirements, the value propagation throughout the development is possible to monitor based on both market and scope changes. In addition, a measure of productivity can be calculated by relating the perceived value to the spent effort. This information is used in order to visualize the value propagation and performance during the development. Hence, through this method it is possible to evaluate the productivity of activities from initial ideas to a final product. The paper is concluded with a discussion of managerial implications and how this method contributes to theory.

The run-time context in industrial embedded systems varies from bare-metal microcontrollers, to multicore-processors running real-time operating systems. Due to the longevity of industrial systems, reusability and evolvability are often considered crucial quality attributes. This paper presents a new flexible task design that enables tasks to be agnostic to run-time context. Evaluations of the design were made by conducting experiments using a proof of concept implementation of the proposed design. The experiments were based on typical industrial constructs, such as periodic tasks, and event signaling from interrupts. Findings from the experiments show that tasks can be more agnostic to run-time context and still deliver functionality normally used within industry. The results indicate that it is feasible to improve reusability and evolvability between different run-time contexts, and in addition, support hybrid configurations that can reduce resource usage, since e.g. a thread can be easily shared among several tasks.

Most evaluations of industrial real-time software are conducted on real embedded systems. The use of simulators that provides easily reproducible evaluations is often limited, due to different levels of abstraction, e.g., programming languages and run-time contexts. This paper extends previous work on a flexible task design, enabling tasks to be agnostic to run-time context, with evaluations conducted on bare-metal and real-time operating systems. Based on the same design and experiments we extend the proof-of-concept implementation in a discrete event simulation context, executing on a Windows based simulation host. Our experiments show that the flexible task design can be driven in a simulation run-time context, and still support typical industrial constructs. The result indicates that improved code reuse between discrete event simulators and industrial embedded systems is feasible.

In order to facilitate deterministic behavior; industrial real-time communication stacks need another design than non-real-time communication stacks typically found in e.g., Internet of Things and Cloud solutions. We propose a flexible stack design that enable code reuse between testbeds and simulators, as well as how stack layers are driven and prioritized. The design can be generalized and used for non-real-time bare-metal solutions like battery powered Internet of Things. Our approach aims at extending the use of simulation during development of industrial systems in order to find logical errors and wrong assumptions earlier in the development. Conducted and evaluated experiments show that the proposed solutions are able to extend the use of simulation during development of real-time communication software. This is achieved by reusing the same code on an industrial testbed and in a discrete event simulator. In addition, the experiments show that the stack design is generalizable and enable reuse with other non-real-time embedded systems. The contribution consists of a set of building blocks for real-time systems that enable control over the system timing when executing on a simulation host while reusing the source code from an industrial testbed. Overall, this will improve the engineering situation, with respect to code reuse, flexibility and debugging. © 2023 The Author(s)

Industrial real-time software is commonly evaluated on real embedded systems, while simulators are less used, since the abstraction level and purpose vary with for example, different programming languages and run-time contexts. This paper extends, applies, and evaluates previous work on a flexible task design that improve code reuse between discrete event simulators and embedded real-time systems. The paper focuses on two parts: (i) The performance cost of the proposed design in practice, by comparing the flexible task design with a traditional threaded approach. (ii) The potential of an alternative way to support legacy code in combination with discrete event simulation. The experiments indicate an almost negligible performance cost with respect to the real-time behavior, i.e., latency and jitter, while enabling improved code reuse between discrete event simulation and industrial embedded real-time systems.

Engineering system architectures for complex systems involves the tasks of analyzing architectural drivers, identifying architectural concerns, identifying valid architecture candidates, and evaluation of alternatives. One problem to overcome when architecting a system is the identification of valid of architectural candidates. We have developed a step-wise method for performing system architecture analysis and tested it on a sub-system in a project developing a drive system for heavy automotive applications. In this paper we present the complete method of nine steps for engineering an architecture and we elaborate in detail on the procedure to identify architectural candidates based on previously identified architectural drivers. We present a diagram depicting the proposed information model, its concepts and their relationships. In addition, the expectations on such a method as expressed by practitioners have been elicited, and we elaborate on the validity by examining how well the method indicate fulfillment. Our conclusion is that the proposed method does not fail to deliver on any of the needs and this gives an indication of usefulness. When identifying architectural candidates it is important to use proper criteria in the process. Our conclusion is that the practitioners should focus on candidates that affect the system at hand (within system boundaries), and on the candidates that address the architecturally significant system use. This is reflected in our method where we prescribe evaluation of the design candidates by validating that they solve only the right problem and by ensuring that they address the system at hand.

A modern mine involves increasingly smart and connected products that are integrated in a mine automation system. Integration enable many possible applications that could substantially aid in achieving the goals of increased safety and productivity of the mine operation including the machine maintenance process. What data will be shared by the involved organizations and products, heavily affects how successful improvements of operation can be accommodated. We have devised a method to map out and evaluate envisioned new collaborative functions for a complex System-of-systems such as the mine maintenance operation. The proposed method map user stories for the involved stakeholders and estimate the value of fulfillment based on different candidates of data sharing architectures. The method is explained and exemplified by a realistic example based the real case. There seems to be a need for a method such as the presented one just to map out what new applications are really feasible. By estimating value in terms of stakeholder benefits and identifying possible showstoppers in terms of protected data, the method seems to help reveal what improvements in the mine operation is in fact possible. Deciding on a data-sharing architecture for a collaborative mine seems to provide useful design prerequisites to a developing organization improving their smart connected products.

Embedded systems are today often self-sufficient with limited and predefined communication. However, this traditional view of embedded systems is changing through advancements in technologies such as, communication, cloud technologies, and advanced analytics including machine learning. These advancements have increased the benefits of building Systems of Systems (SoS) that can provide a functionality with unique capabilities that none of the included subsystems can accomplish separately. By this gain of functionality the embedded system is evolving towards a “dual use” purpose¹¹In this paper we define dual usage as a control system having two purposes. In other contexts such as politics, diplomacy and export control, the term “dual-use” refers to technology that can be used for both peaceful and military aims, e.g., nuclear power technology., The use is dual in the sense that the system still needs to handle its original task, e.g., control and protect of an asset, and it must provide information for creating the SoS. Larger installations, e.g., industry plants, power systems and generation, have in most cases a long expected life-cycle, some up to 30–40 years without significant updates, compared to analytical functions that evolve and change much faster, i.e., requiring new types of data sets from the subsystems, not know at its first deployment. This difference in development cycles calls for new solutions supporting updates related to new requirements inherent in analytical functions. In this paper, within the context of “dual usage” of systems and subsystems, we analyze the impact on an embedded system, new or legacy, when it is required to provide analytic data with high quality. We compare a reference system, implementing all functions in one CPU core, to three other alternative solutions: a) a multi-core system where we are using a separate core for analytics, b) using a separate analytics CPU and c) analytics functionality located in a separate subsystem. Our conclusion is that the choice of analytics information collection method should to be based on intended usage, along with resulting complexity and cost of updates compared to hardware cost.

Embedded systems are today often self-sufficient systems with limited communication. However, this traditional view of an embedded system is changing rapidly. Embedded systems are nowadays evolving, e.g., an evolution pushed by the increased functional gain introduced with the concept of System of Systems (SoS) that is connecting multiple subsystems to achieve a combined functionality and/or information of a higher value. In such a SoS the subsystems will have to serve a dual purpose in a) the initial purpose that the subsystem was originally designed and deployed for, e.g., control and protection of the physical assets of a critical infrastructure system that could be up and running for 30-40 years, and b) at the same time provide information to a higher-level system for a potential future increase of system functionality as technology matures and/or new opportunities are provided by, e.g., greater analytics capabilities. In this paper, within the context of a “dual purpose use” of a) and b), we bring up three central challenges related to i) information gathering, ii) life-cycle management, and iii) data governance, and we propose directions for solutions to these challenges that need to be evaluated already at design time.

De närmaste 15 åren kommer svenskindustri att med förnyad kraft fortsätta sin digitala omställning, ta tillsig en rad nya material, utveckla nyaaffärsmodeller och öka sin transformationsförmåga. Allt för att stärkasin konkurrenskraft, i symbios medhållbarhet – ekonomisk, ekologisk ochsocial. Coronapandemin medför förvisso enorma utmaningar för industrin,men efter den akuta kris hanteringenkommer med all sannolikhetindustriomställningen att ta ny fart.

Denna broschyr är en förkortad sammanställning av RISE rapport 2020:46 som finns på länken:http://urn.kb.se/resolve?urn=urn:nbn:se:ri:diva-44978

Detta projekt har haft som mål att undersöka möjligheten att genomföra ett FUI-projekt som fokuserar på hur framtidens service- och underhållstekniker arbetar. Projektet har undersökt fler processindustrier för att kartlägga synergier mellan olika branscher vad gäller innovationer och förbättringar för framtidens service- och underhållstekniker. Projektet har drivits av SICS Swedish ICT i samarbete med SSAB och ABB Service. Prevas och ATM Notation har dessutom deltagit som leverantör av varor och tjänster. Projektet har stämt av deltagarnas visioner mot existerande underhållslösningar och tillgänglig teknik. Vi har också identifierat behov av ytterligare innovationer inom processer, metoder och teknik. Projektet ingår i Strategiska innovationsprogrammet Processindustriell IT och Automation, PiiA, med stöd från VINNOVA.

In industrial software testing, development projects typically set up and maintain test suites containing large numbers of test cases. Executing a large number of test cases can be expensive in terms of effort and wall-clock time. Moreover, indiscriminate execution of all available test cases typically lead to sub-optimal use of testing resources. On the other hand, selecting too few test cases for execution might leave a large number of faults undiscovered. Limiting factors such as allocated budget and time constraints for testing further emphasizes the importance of test case prioritization in order to identify test cases that enable earlier detection of faults while respecting such constraints. In this paper, we propose a multi-criteria decision making approach for prioritizing test cases in order to detect faults earlier. This is achieved by applying the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) decision making technique combined with fuzzy principles. Our solution is based on important criteria such as fault detection probability, execution time, complexity, and other test case properties. By applying the approach on a train control management subsystem from Bombardier Transportation in Sweden, we demonstrate how it helps, in a systematic way, to identify test cases that can lead to early detection of faults while respecting various criteria.

In software system development, testing can take considerable time and resources, and there are numerous examples in the literature of how to improve the testing process. In particular, methods for selection and prioritization of test cases can play a critical role in efficient use of testing resources. This paper focuses on the problem of selection and ordering of integration-level test cases. Integration testing is performed to evaluate the correctness of several units in composition. Further, for reasons of both effectiveness and safety, many embedded systems are still tested manually. To this end, we propose a process, supported by an online decision support system, for ordering and selection of test cases based on the test result of previously executed test cases. To analyze the economic efficiency of such a system, a customized return on investment (ROI) metric tailored for system integration testing is introduced. Using data collected from the development process of a large-scale safety-critical embedded system, we perform Monte Carlo simulations to evaluate the expected ROI of three variants of the proposed new process. The results show that our proposed decision support system is beneficial in terms of ROI at system integration testing and thus qualifies as an important element in improving the integration testing process.

Prioritization, selection and minimization of test cases are well-known problems in software testing. Test case prioritization deals with the problem of ordering an existing set of test cases, typically with respect to the estimated likelihood of detecting faults. Test case selection addresses the problem of selecting a subset of an existing set of test cases, typically by discarding test cases that do not add any value in improving the quality of the software under test. Most existing approaches for test case prioritization and selection suffer from one or several drawbacks. For example, they to a large extent utilize static analysis of code for that purpose, making them unfit for higher levels of testing such as integration testing. Moreover, they do not exploit the possibility of dynamically changing the prioritization or selection of test cases based on the execution results of prior test cases. Such dynamic analysis allows for discarding test cases that do not need to be executed and are thus redundant. This paper proposes a generic method for prioritization and selection of test cases in integration testing that addresses the above issues. We also present the results of an industrial case study where initial evidence suggests the potential usefulness of our approach in testing a safety-critical train control management subsystem.

Context: Today, software and embedded systems act as enablers for developing new functionality in traditional industries such as the automotive, process automation, and manufacturing automation domains. This differs from 25–30 years ago when these systems where based on electronics and electro-mechanical solutions. The architecture of the embedded system and of the software is important to ensure the qualities of these applications. However, the effort of designing and evolving the architecture is in practice often neglected during system development, whilst development efforts are centered on implementing new functionality. Objective: We present problems and success factors that are central to the architectural development of software intensive systems in the domain of automotive and automation products as judged by practitioners. Method: The method consisted of three steps. First, we used semi-structured interviews to collect data in an exploratory manner. As a second step, a survey based on problems extracted from the interview data was used to investigate the occurrence of these problems at a wider range of organizations. In order to identify and suggest how to mitigate the problems that were considered important, we finally performed root cause analysis workshops, and from these a number of success factors were elicited. Results: A total of 21 problems have been identified based on the interview data, and these are related to the technical, organizational, project, and agreement processes. Based on the survey results, the following four problems were selected for a root cause analysis: (1) there is a lack of process for architecture development, (2) there is a lack of method or model to evaluate the business value when choosing the architecture, (3) there is a lack of clear long-term architectural strategy, and (4) processes and methods are less valued than knowledge and competence of individuals. Conclusion: In conclusion, the following identified success factors are crucial components to be successful in developing software intensive systems: (1) define an architectural strategy, (2) implement a process for architectural work, (3) ensure authority for architects, (4) clarify the business impact of the architecture, and (5) optimize on the project portfolio level instead of optimizing each project.