Michael MasinIBM Research - Haifa · Systems Engineering Technologies
Michael Masin
PhD
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46
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820
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Citations since 2017
Publications
Publications (46)
We address the problem of synthesizing safety-critical embedded and cyber-physical system architectures to minimize a cost function while guaranteeing the desired reliability. We represent a system architecture as a configurable graph in which both the nodes (components) and edges (interconnections) may fail. We then propose a compact analytical fo...
Deep learning (DL) algorithms have already proved their effectiveness on a wide variety of application domains, including speech recognition, natural language processing, and image classification. To foster their pervasive adoption in applications where low latency, privacy issues and data bandwidth are paramount, the current trend is to perform in...
Cyber-Physical Systems (CPS) are embedded computational collaborating devices, capable of sensing and controlling physical elements and, often, responding to humans. Designing and managing systems able to respond to different, concurrent requirements during operation is not straightforward, and introduce the need of proper support at design-time an...
Technical Requirements (TRs) provide a "black box" conceptualization of the target project results with explicit verification tests. The goal of Technical Requirements Elicitation (TRE) is to ensure that all needs of involved stakeholders are being identified and adequately addressed without prescribing how to achieve them. Whilst TRE methodology i...
Novel Deep Learning (DL) algorithms show ever-increasing accuracy and precision in multiple application domains. However, some steps further are needed towards the ubiquitous adoption of this kind of instrument. First, effort and skills required to develop new DL models, or to adapt existing ones to new use-cases, are hardly available for small- an...
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Model-based design methodologies are commonly used in industry for the development of complex cyber-physical systems (CPSs). There are many different languages, tools, and formalisms for model-based design, each with its strengths and weaknesses. Instead of accepting some weaknesses of a particular tool, an alternative is to embrace heterogeneity,...
Multi-objective optimization problems involve more than one objective to be optimized simultaneously. Typically however, there is no single solution that simultaneously optimizes them all. This can be overcome by calculating a set of compromise solutions, called the Pareto frontier. We hereby introduce a new approach, called Set-SMAA. It extends st...
In the last few years, besides the concepts of embedded
and interconnected systems, also the notion of Cyber-
Physical Systems (CPS) has emerged: embedded computational
collaborating devices, capable of sensing and controlling physical
elements and, often, responding to humans. The continuous interaction
between physical and computing layers makes...
The impact of systems engineering on program cost has been recognized for over a decade. From the very early stages, careful management of the relationships between the product design and the project plan is crucial to the success of any project that aims to deliver a defined product. Failure to closely manage the intricate web of resource constrai...
A novel and useful system and method of decentralized decision-making for real-time scheduling in a multi-process environment. For each process step and/or resource capable of processing a particular step, a service index is calculated. The calculation takes into account several measures, such as business level measures, operational measures and em...
This paper defines a suite of requirements for future hybrid cosimulation standards, and specifically provides guidliance for development of a hybrid cosimulation version of the Functional Mockup Interface (FMI). A cosimulation standard defines interfaces that enable diverse simulation tools to interoperate. Specifically, one tool defines a compone...
Maintaining coherence between system functional, performance, production and operational requirements is a key to the ability to optimize the design of large-scale systems. Different architectural configurations entail significant differences in functionality, performance, ease of manufacturing/assembly and operational behavior. While the first two...
The data of real-world optimization problems are usually uncertain, that is especially true for early stages of system design. Data uncertainty can significantly affect the quality of the nominal solution. Robust Optimization (RO) methodology uses chance and robust constraints to generate a robust solution immunized against the effect of data uncer...
Systems and methods for scheduling events in a virtualized computing environment are provided. In one embodiment, the method comprises scheduling one or more events in a first event queue implemented in a computing environment, in response to determining that number of events in the first event queue is greater than a first threshold value, wherein...
Domain experience is a key driver behind design quality, especially during the early design phases of a product or service. Currently, the only practical way to bring such experience into a project is to directly engage subject matter experts, which means there is the potential for a resource availability bottleneck because the experts are not avai...
We study a generalized version of the minimum makespan jobshop problem in which multiple instances of each job are to be processed. The system starts with specified inventory levels in all buffers and finishes with some desired inventory levels of the buffers at the end of the planning horizon. A schedule that minimizes the completion time of all t...
Model-Based Systems Engineering (MBSE) is making its way into the design processes of many Systems builders. As with many other disciplines, MBSE can greatly benefit from the principles of reuse, but the very term assumes the existence of a large number of available models which may not be available due to the newness of MBSE activities. There exis...
A method of interactively achieving a Pareto-optimal design of systems is provided herein. The method includes the following stages: generating a system model containing elements that are associated with design parameters and design alternatives, as well as directives for calculating the system's measures of effectiveness (being the optimization ob...
We consider two complementary tasks for consuming optimization results of a given multiobjective problem by decision-makers. The underpinning in both exploratory tasks is analyzing Pareto landscapes, and we propose in both cases discrete graph-based reductions. Firstly, we introduce interactive navigation from a given suboptimal reference solution...
Viewpoint modeling is an effective approach for analyzing and designing complex systems. Splitting various elements and corresponding constraints into different perspectives of interests, enables separation of concerns such as domains of expertise, levels of abstraction, and stages in lifecycle. Specifically, in Systems Engineering different viewpo...
Creation and management of large complex systems of systems (SoS) can be a daunting task for even the most experienced engineers. Architecting these systems requires considerable domain expertise and next generation tools to seamlessly link requirements elicitation, through to modeling and simulation, and finally through to implementation. The resu...
In this paper, we explain how to achieve deterministic execution of FMUs (Functional Mockup Units) under the FMI (Functional Mockup Interface) standard. In particular, we focus on co-simulation, where an FMU either contains its own internal simulation algorithm or serves as a gateway to a simulation tool. We give conditions on the design of FMUs an...
This paper considers the problem of finding architectures with sufficient multi-objective Pareto optimality and maximum diversity of their design-variable values. This problem has been exclusively addressed to date by Evolutionary Algorithms, which are known to be powerful, and yet, the optimality of their solutions cannot be guaranteed. This paper...
A more recent trend in Systems Engineering is architecture optimization. Evermore complex aircraft systems make it harder and harder to determine, with reasonable time and effort, optimal architectures by traditional trial-and-error trade off studies. This can be alleviated by architecture optimization techniques where System Engineers only defines...
The complexity of contemporary systems causes Systems Engineers great pains during early architectural design phases. Model-Based Systems Engineering (MBSE) proposes methodologies to deal with complexity and streamline design processes, but the penetration of the new approach is slow. This paper proposes a generic SysML based methodology for improv...
In this work, we optimize the admission policy of application deployment requests submitted to data centers. Data centers are typically comprised of many physical servers. However, their resources are limited, and occasionally demand can be higher than what the system can handle, resulting with lost opportunities. Since different requests typically...
Lot splitting is a new approach for improving productivity by dividing production lots into sublots. This approach enables accelerating production flow, reducing lead-time and increasing the utilization of organization resources. Most of the lot splitting models in the literature have addressed a single objective problem, usually the makespan or fl...
A new simulation-based feedback control algorithm, called Adaptive Work In Process (AWIP), for the design of Self-regulating Production Control Systems (SPCSs) such as Kanban, CONWIP, base stock control and their generalizations is presented. The problem of minimizing average Work In Process (WIP) subject to a required throughput is solved. The AWI...
One of the most common approaches for multiobjective optimization is to generate the whole or partial efficient frontier and then decide about the preferred solution in a higher-level decision-making process. In this paper, a new method for generating the efficient frontier for multiobjective problems is developed, called the diversity maximization...
In this chapter, we present operational and planning models for manufacturing systems. These models are developed to show
the operational fidelity of the models to various manufacturing processes. The models are initially used to plan production
activities for a variety of products that will be semi-automatically manufactured. The same models are t...
In complex manufacturing environments, meeting the due dates of the jobs and minimizing in process inventories are important performance metrics. One of the common characteristics of complex production systems is production-assembly network of operations. This paper presents an auction-based algorithm for simultaneous scheduling of all manufactured...
Usually each manufacturing stage in a supply chain makes its own decision regarding quantity and timing of parts it purchases from its suppliers, thereby controlling its inventory position and overall supply chain dynamics. Such decisions, although good for each individual stage, can adversely affect the overall performance of the supply chain. Thi...
Self-regulating Production Control Systems (SPCSs) include production control systems such as kanban, buffered lines, base-stock, and their variations and combinations. In this work we develop and implement, for SPCS design, a new simulation-based optimization method called Tradeoffs Programming (TOP). TOP is a technique closely related to multi-ob...
This paper presents a design methodology for assembly systems based on teams, where each team is semi-autonomous with well-defined responsibilities. Team oriented assembly systems meet new objectives of modern assembly systems. At the same time, they also create a more satisfactory work environment. The design decisions include the number of teams,...
In this paper, the mean flowtime and the makespan objectives are simultaneously investigated in a single product, m-machine, flowshop system. For this purpose, an efficiency frontier approach is applied and an optimal algorithm for generating all efficient solutions is developed. A comprehensive computational experiment is performed for analyzing t...
The past two decades have seen significant improvements in optimization modeling and software solvers for large-scale optimization problems, especially discrete problems. We feel that a critical feature of many of these systems is being overlooked. That is, the process control engineer adjusts process parameters while only considering the local eff...
A new multi-objective approach for the cell formation problem in a lumpy demand environment is presented. The objectives addressed in this paper are grouping efficiency and capacity requirements. In lumpy demand the required capacity is affected by demand variability and the correlation between the part types assigned to the cells. We claim that si...
This research focuses on CONWIP, a closed production control system where all containers traverse a circuit incorporating the entire production line. We develop estimates, for an important level of work in process inventory, for four important performance measures: the means and variances of time between departures and flowtime. We develop our esti...
This research focuses on CONWIP, a closed production control system where all containers traverse a circuit incorporating the entire production line. We develop estimates, for an important level of work in process inventory, for four important performance measures: the means and variances of time between departures and flowtime. We develop our esti...
CONWIP (CONstant Work In Process) has been proposed as a new production management technique. CONWIP is a closed production management system in which a fixed number of containers traverses a circuit that includes the entire production line. This paper develops a mathematical programming formulation of a CONWIP-based production system that solves t...
Projects
Projects (3)
http://www.cerbero-h2020.eu/
The Cross-layer modEl-based fRamework for multi-oBjective dEsign of Reconfigurable systems in unceRtain hybRid envirOnments (CERBERO) project aims at developing a design environment for CPS based of two pillars: a cross-layer model based approach to describe, optimize, and analyze the system and all its different views concurrently; an advanced adaptivity support based on a multi-layer autonomous engine. To overcome the limit of current tools, CERBERO provides: libraries of generic Key Performance Indicators for reconfigurable CPSs in hybrid/uncertain environments; novel formal and simulation-based methods; a continuous design environment guaranteeing early-stage analysis and optimization of functional and non-functional requirements, including energy, reliability and security.
