Purpose: The study examines the remote integration process of advanced manufacturing technology (AMT) into the production system and identifies key challenges and mitigating actions for a smoother introduction and integration process.Design/methodology/approach: The study adopts a case study approach to a cyber-physical production system at an industrial technology center using a mobile robot as an AMT.Findings: By applying the plug-and-produce concept, the study exemplifies an AMT's remote integration process into a cyber-physical production system in nine steps. Eleven key challenges and twelve mitigation actions for remote integration are described based on technology–organization–environment theory. Finally, a remote integration framework is proposed to facilitate AMT integration into production systems.Practical implications: The study presents results purely from a practical perspective, which could reduce dilemmas in early decision-making related to smart production. The proposed framework can improve flexibility and decrease the time needed to configure new AMTs in existing production systems.Originality/value: The area of remote integration for AMT has not been addressed in depth before. The consequences of lacking in-depth studies for remote integration imply that current implementation processes do not match the needs and the existing situation in the industry and often underestimate the complexity of considering both technological and organizational issues. The new integrated framework can already be deployed by industry professionals in their efforts to integrate new technologies with shorter time to volume and increased quality but also as a means for training employees in critical competencies required for remote integration.

To combine the relative strengths of fully preemptive and non-preemptive fixed priority scheduling, we can use limited preemptive scheduling methods. One such method is fixed-priority threshold scheduling (FPTS). This approach defines dual priorities for every task, a priority assigned to the inactive jobs and an equal or a higher one, called preemption threshold, for the jobs that have already started executing. A task can preempt another task's job if and only if its priority is greater than the other task's preemption threshold. FPTS can be implemented by assigning tasks to non-preemptive groups in a one-to-many manner. That is groups of tasks that are mutually non-preemptive.

Fixed-priority preemption-threshold scheduling (FPTS) is a generalization of fixed-priority preemptive scheduling (FPPS) and fixed-priority non-preemptive scheduling (FPNS). Since FPPS and FPNS are incomparable in terms of potential schedulability, FPTS has the advantage that it can schedule any task set schedulable by FPPS or FPNS and some that are not schedulable by either. FPTS is based on the idea that each task is assigned a priority and a preemption threshold. While tasks are admitted into the system according to their priorities, they can only be preempted by tasks that have priority higher than the preemption threshold. This paper presents a new optimal priority and preemption threshold assignment (OPTA) algorithm for FPTS which in general outperforms the existing algorithms in terms of the size of the explored state-space and the total number of worst case response time calculations performed. The algorithm is based on back-tracking, i.e. it traverses the space of potential priorities and preemption thresholds, while pruning infeasible paths, and returns the first assignment deemed schedulable. We present the evaluation results where we compare the complexity of the new algorithm with the existing one. We show that the new algorithm significantly reduces the time needed to find a solution. Through a comparative evaluation, we show the improvements that can be achieved in terms of schedulability ratio by our OPTA compared to a deadline monotonic priority assignment.

In this paper, we present a tool for performing trade-off analysis of Quality-of-Service attributes of design solutions resulted from architectural, behavioral, or deployment changes in service-oriented systems. The tool allows for comparing the performance, reliability, and maintainability of such solutions, in an attempt to compute the optimal one with respect to the weighted sum of the considered quality attributes. Our tool uses the Analytic Hierarchy Process for computing these trade-offs and is integrated into the Quality Impact Prediction for Evolving Service-Oriented Software IDE. Consequently, architects and system analysts now have an easy to use tool set for making trade-offs for these system qualities.

Fixed priority preemption threshold scheduling (FPTS) may significantly improve the schedulability ratio of task sets compared to both fixed-priority pre-emptive scheduling (FPPS) and fixed-priority non-preemptive scheduling (FPNS). Moreover, FPTS reduces stack memory requirements compared to FPPS. Unfortunately, the scheduling policy defined by the standard automotive platform AUTOSAR/OSEK only supports a restricted version of FPTS. In earlier work, the consequences of these limitations have been investigated for the schedulability ratio of task sets on a uniprocessor platform. This paper considers the consequences for the stack memory requirements. To that end, it presents a preemption threshold assignment algorithm for minimizing stack usage under FPTS on an AUTOSAR/OSEK platform. The paper includes a comparative evaluation of the stack usage of FPTS without restrictions and FPTS as defined by AUTOSAR/OSEK.