Wilfried Sihn

• Fraunhofer Austria Research GmbH

This paper presents the development and evaluation of a digital planning method for the operational purchasing that enables an automated and product-specific optimized material requirements planning. With materials planning today facing a volatile and complex market environment, the trend towards automated processes in procurement is the key to com...

In contrast to the linear production model, the circular economy aims to close the loop of materials. One part of this approach is remanufacturing, which extends the lifetime of products. Various stakeholders in the supply chain are involved in remanufacturing. This makes the management and optimization of remanufacturing activities complex. The da...

Maintenance planning in Industry 4.0 gains benefits from symbolic AI for knowledge representation learning from heterogeneous data. Traditionally simulation models are utilized that are not flexible to cope with dynamic changes and to react to ad-hoc events. This paper presents a novel competence-based maintenance planning (CBMP) methodology using...

The reliability of production plans drops drastically within several days after plan creation. The reasons for the deviation between planning and execution are manifold. Causes can be e.g., uncertainties, inaccurate or insufficient planning data (e.g., data quality and availability), inappropriate planning and control models and systems or unforese...

Industrial management is facing many challenges, one need is to adopt sustainable practices. As climate change is becoming an increasingly urgent problem, industrial management must find ways to reduce waste and pollution, conserve natural resources, and protect the environment and employees. Industrial management also needs to embrace new technolo...

Präzise Bedarfsprognosen sind der Schlüssel für eine erfolgreiche Materialdisposition. EntscheidungsträgerInnen stehen jedoch vor dem Dilemma, welches Prognoseverfahren sie verwenden sollen. Zumeist fehlt auch das Methodenwissen, um komplexe mathematische Prognoseverfahren anwenden zu können. Doch auch nach der Wahl des Prognoseverfahrens verbleibt...

Maintenance orders are difficult to plan and require a high degree of flexibility, because both the extent of the activity ("What needs to be done?"), the scheduling ("When is the repair to be carried out?") and spatial restrictions ("Where is the repair to be carried out?") are largely unknown at the beginning of an order. All this results in a wi...

For decades, different approaches have been designed and implemented for optimizing maintenance management systems in manufacturing. Especially advancing digitalization is leading to novel data-driven maintenance methods and strategies. However, the envisaged value-added implementation of novel solutions faces several challenges in the industrial c...

This paper presents a digital material planning approach, utilizing simulation-based optimization to select and parametrize article specific demand forecasting methods. Demand forecasts are the basis of material requirements planning in consumption-based material planning, and are an essential lever for efficient inventory and order calculation. De...

This paper presents a material requirements planning method that determines optimal safety stock levels using a heuristic optimization, based on a deterministic simulation of stock levels. Material requirements planning is a key competitiveness factor in a volatile, global market environment and is becoming increasingly complex due to the availabil...

Individual usage profile (aka true usage profile) of military logistic vehicles (MLV) is highly dependent on types of operations, duration and areas of use. Compared to non-military vehicles, the operation life is considerably longer, mileage tends to be several times lower and the characteristics of the application area, including environmental fa...

Abstract Taking up the fact that the increasing pace of innovation and technological change have an essential influence on the development of components and their market availability, system manufacturers are increasingly struggling to ensure the long-term availability of the corresponding hardware and software. In this article, a holistic obsolesc...

Advancing digitalization is leading to new opportunities in maintenance. However, the implementation of data-driven solutions faces several challenges in industrial practice. Bridging the gap between research and practice, this paper proposes a procedural approach that covers the complete development and implementation process and enables industria...

This paper investigates the feasibility and performance of Deep Reinforcement Learning (RL) as a method for optimizing assembly cell configurations in adaptable cell-oriented assembly systems (ACAS). ACAS can be as productive as conventional assembly lines, while offering greater flexibility and resilience. However, optimizing their layout configur...

To enable transparency of assembly systems feedback on physical progress is crucial. However, this currently requires manual operator feedback, which risks reducing the productivity of the assembly system. Technologies such as IoT sensors have been developed to increase the transparency of process states by generating suitable information for furth...

With materials planning today facing a volatile and complex market environment, the trend towards automated processes in procurement is the key to market competitiveness. Digitisation in procurement and especially algorithms for lot-sizing problems can support decisions and achieve major cost savings. Although simulation-based optimisation, based o...

The continuous acquisition of new digital competences and the development of situational learning assistance systems will become more important than ever in the coming years, because the world of work is becoming more complex, more informative and all above more data-driven. Jobs are changing due to increasing digitalisation, whereby the use of mod...

Autonomous production control (APC) is able to deal with challenges, inter alia, high delivery accuracy, shorter planning horizons, increasing product and process complexity, and frequent changes. However, several state-of-the-art approaches do not consider maintenance factors contributing to operational and tactical decisions in production plannin...

The ongoing digitization of the industry leads to new opportunities in industrial maintenance. Several concepts for smart maintenance have been published in literature, however, their application remains limited in industrial practice. To close the existing gap between research and practice, a novel practice-oriented approach is presented. A modifi...

Since the reliability of production plans drops largely within several days after plan creation, production control faces huge challenges, when trying to foresee the work in progress (WIP) level at bottleneck machines and trying to react appropriately. Whereas several researchers applied artificial intelligence to predict lead times or transition t...

The ongoing digital transformation in manufacturing is raising the demand for skilling, re-skilling and upskilling of workforces. At the same time, it largely affects skill mismatches in socio-technical work systems. Industry 4.0’s enabling technologies, especially AI and collaborative robotics offer new ways of learning, which introduce innovative...

This paper proposes a data-driven procedure to improve productivity in make-to-stock manufacturing. By leveraging recent developments in information systems research, the paper addresses manufacturing systems with high process complexity and variety. Specifically, the proposed procedure draws upon process mining to dynamically map and analyse manuf...

The global megatrends of digitization and individualization substantially affect manufacturing enterprises. Assembly workers are exposed to increased process complexity resulting in physical and cognitive workload. Worker guidance systems (WGS) are used to overcome this challenge through output of information regarding what should be done, how it s...

Fluctuating customer demands, expected short delivery times and the need for quick order confirmation creates a fast-paced scheduling environment for modern production systems. In this turbulent scene, using the data provided by intelligent elements of cyber-physical production systems opens up new possibilities for dynamic scheduling. The paper in...

Autonomous production control (APC) is able to deal with challenges, inter alia, high delivery accuracy, shorter planning horizons, increasing product and process complexity, and frequent changes. However, several state-of-the-art approaches do not consider maintenance factors contributing to operational and tactical decisions in production plannin...

Original equipment manufacturers (OEMs), machine operators and suppliers are three main stakeholders in today's industrial asset management lifecycle. Considering high rate of investment and prices to purchase and operationalize secured IoT-based production systems, insurance companies explore contributing into industrial asset management lifecycle...

The realization of digitalization in production companies-currently also referred to as Industry 4.0-aims for reduction of internal value creation costs as well as costs for intercompany collaboration and plays a key role in their current strategy development. However, related strategy research still lacks to provide operationalized digitalization...

This paper introduces an innovative method for multi-objective optimization-based production planning with a rolling horizon for food manufacturing. It features a combination of a heuristic mixed-integer optimization and a metaheuristic optimization. The food industry is characterized by highly fluctuating demand, due to standard and promotion sale...

p class="Abstract">There are always deviations between production planning and subsequent execution. Furthermore, it was found that the reliability of the production plans and thus the planning quality (PQ) can drop down to 25% in the first three days after plan creation. These deviations are caused by uncertainties, e.g. inaccurate or insufficient...

Um die Chancen der Digitalisierung und Automatisierung in der Praxis nutzbar zu machen, sowie um zielgerichtete Handlungsschritte festzulegen, muss der aktuelle Entwicklungsstand der Unternehmen erfasst und bewertet werden. Hierzu die Technische Universität Wien und Fraunhofer Austria Research GmbH eine Statuserhebung unter österreichischen Industr...

Industrial Digitalization and Automation (DA), promoted through new production paradigms such as Industry 4.0 currently dominates the strategies of industrial companies. However, practitioners report various problems while implementing DA into their organizations work-routines. We find underlying problems in missing operational monitoring systems t...

Increased utilization of digital elements and computer assistance in industrial enterprises leads to the acquisition of data encompassing all company levels and areas. Subsequently, manufacturing companies face large amounts of collected data from different sources and in various formats. Today this data is beginning to be viewed as a resource, com...

The realization of digitalization in production companies-currently also referred to as Industry 4.0-aims for reduction of internal value creation costs as well as costs for intercompany collaboration and plays a key role in their current strategy development. However, related strategy research still lacks to provide operationalized digitalization...

The high equipment intensity and complexity of production processes in semiconductor manufacturing leads to challenging requirements regarding plant availability in this competitive market. In the present paper, we address these challenges by proposing a conceptual model to enable prescriptive maintenance in semiconductor manufacturing. Different M...

In today’s production environment, change is an integral part of all aspects of production planning and control. Adaptable cell-oriented assembly systems can be equally efficient as conventional assembly lines. While, the former provides significantly more flexibility, contributing to the inevitable transition to more productive and variant-oriente...

Original equipment manufacturers (OEMs), machine operators and suppliers are three main stakeholders in today’s industrial asset management lifecycle. Considering high rate of investment and prices to purchase and operationalize secured IoT-based production systems, insurance companies explore contributing into industrial asset management lifecycle...

The utilization of Digitalization and Automation (DA) is currently one of the determining factors of increasing prosperity, productivity, and efficiency. Although widely promoted and incentivized by policy- and decision makers, industrial enterprises seem reluctant to actively push DA-development in their organizations. From a scientific point of v...

In the light of rapid technological enhancements and digitalization, complex process-related, technical and organizational interdependencies and correlations in production and logistics can no longer be grasped and resolved by domain experts exclusively. Modern data science methods and technologies, e.g. advanced machine learning, are needed to ove...

The digital transformation of manufacturing industries currently re-invents conventional production paradigms through the creation of cyber-physical production systems (CPPS) and smart manufacturing networks. Novel knowledge-based maintenance (KBM) strategies and models are regarded as a key enabler in order to manage the increasing complexity and...

Emerging technologies from the fields of communication, digitization and automation are available for various business applications. They enable the development of new business models. However, their implementation entails risks: On the one hand, it has to be invested into widely unknown technologies and infrastructure, on the other hand, revenues...

Collaborative applications, where humans and robots work in a pre-defined workspace at the same time, are characterized by flexible task allocation patterns. Here, task allocation is dependent on the required degree of automation as well as on the demands by the individual processes and provided abilities by the collaborative resources. The dynamic...

Eine hohe Prozessstabilität und Produktqualität ist für viele Unternehmen entscheidend, um in einem sehr kompetitiven Markt konkurrenzfähig zu bleiben. Vor dem Hintergrund der digitalen Transformation der Produktion werden an Produktionsanlagen eine Vielzahl an Prozess- und Qualitätsdaten erfasst, verarbeitet und gespeichert. In diesem Zusammenhang...

Autonomous production control models facilitate coping with co-occurrent and ever-growing production system complexity. The choice of the appropriate control model and objective function in manufacturing industry depends on several interrelated factors such as machine and process flexibility, plant availability, process stability, resource utilizat...

Predicting unscheduled breakdowns of plasma etching equipment can reduce maintenance costs and production losses in the semiconductor industry. However, plasma etching is a complex procedure and it is hard to capture all relevant equipment properties and behaviors in a single physical model. Machine learning offers an alternative for predicting upc...

Autonome Produktionsumgebungen führen tendenziell zu weniger Interaktion mit zunehmend selbstgesteuerten Prozessen und bieten weniger Gelegenheit für menschliches Lernen. Das vorgestellte Konzept für ein Assistenzsystem zum arbeitsplatznahen, reziproken Ler-nen zielt auf die gleichzeitige Verbesserung der Fähigkeiten von auto-nomen Systemen und Men...

Semiconductor electronics is a highly globalized, competitive, high-volume and low-cost manufacturing sector that has experienced continuous outsourcing to specialized Electronic Manufacturing Services (EMS) and offshoring during the last decades. While large portions of the value stream have been automated, EMS struggle to rationalize production o...

Digital transformation and evolution of integrated computational and visualisation technologies lead to new opportunities for reinforcing knowledge-based maintenance through collection, processing and provision of actionable information and recommendations for maintenance operators. Providing actionable information regarding both corrective and pre...

Currently, no proper cost models are available to assist managers in selecting part-specific allocation strategies for spare parts under consideration of metal additive manufacturing (AM). Therefore, sustainability aspects and cost efficiency over a product lifecycle show potential for optimisation. The aim of this paper is to propose a two-stage m...

Condition Monitoring (CM) and production planning and scheduling (PPS) are well-known and broadly discussed topics. Considering a machine’s condition within short-term PPS may lead to a more realistic model of a production system and is therefore supporting production planners at their complex tasks of scheduling and sequencing. Despite the foresee...

One of the most important objectives in assembly line balancing is to evenly distribute the workload of the stations. In the literature different measures were developed for evaluating the balance quality of an assignment. However, because of the complexity of the defined indices they are rarely studied with exact methods of assembly line balancing...

This paper explores the concept of mutual (reciprocal) learning as an enabler of the emergence of a collective human-machine intelligence across a smart factory. The interlinking of digital profiles of humans and machines permits the identification and measurement of learning outcomes through participating in and performing of (shared) tasks. To ac...

Cyber physical social systems (CPSS) tend to integrate computation with physical processes as well as human and social characteristics. The fusion of cyber, physical, and socio spaces through Industry 4.0 emerges a new type of production systems known as cyber physical production systems (CPPS). CPPS enriches communications among cyber-physical-soc...

Although industrial decision makers show increased readiness to invest in their company’s digital transformation – currently referred to as Industry 4.0, they lack knowledge regarding their current status in Industry 4.0 and strategic guidance towards its realization. In this paper, we present a holistic procedure model that guides manufacturing co...

The main objective of this paper is to examine transferability of “Decision-Making tasks” between human and Cyber-Physical Production Systems (CPPS), in which the focus is on complementarity of human-CPPS in contrast to substitutability. We hold a hybrid approach combining qualitative and quantitative models to investigate human competence levels a...

In recent years, the number of hybrid work systems using human robot collaboration (HRC) increased in industrial production environments – enhancing productivity while reducing work-related burden. Despite growing availability of HRC-suitable manipulation and safety technology, tools and techniques facilitating the design, planning and implementati...

The state of the art literature of condition monitoring (CM) and predictive maintenance does not reflect adequate industry-oriented approaches, which address the integration of CM within production scheduling in production management systems. Addressing this problem, the present paper proposes a novel approach for a machine tool condition based pro...

The paradigm shift in production system known as Industry 4.0 imposes changes on work division between human and machine. A human labor on the one side is assisted by smart devices and machines (human-machine cooperation) and on the other should interact and exchange information with intelligent machines (human-machine collaboration). This paper ad...

Current production planning and control systems of manufacturing companies do not include future-oriented maintenance strategies that allow the precise prediction of maintenance tasks. This results in inefficient production processes due to unforeseeable machine downtimes, fluctuating lead times and a high number of rush orders. An approach for the...

Collaboration across organizational, business and technological borders receives growing emphasis in industrial production due to the evolution of production networks, as well as the growing integration of different product life cycle stages. These demands receive growing attention in the learning factory community, and can be answered by the combi...

Constantly changing assembly tasks and reduced production cycles increase the risk of cognitive stress of operators. A large number of digital assistance systems implemented in assembly lines contribute to operator’s stress reduction. However, small and medium sized companies confront major challenges in implementing digital assistance solutions du...

The Digital Twin (DT) is commonly known as a key enabler for the digital transformation, however, in literature is no common understanding concerning this term. It is used slightly different over the disparate disciplines. The aim of this paper is to provide a categorical literature review of the DT in manufacturing and to classify existing publica...

Die Erwartungen der Kunden sind in den letzten Jahren, vor allem durch technologische Entwicklungen und damit verbundenen digitalen Angeboten, enorm gestiegen. Dieser Ruf nach einer umfassenden Digitalisierung der angebotenen Leistungen weitet sich nach den Vorreiterbranchen, wie dem Handel oder der Medienbranche, mittlerweile auf alle Branchen der...

In production research, sustainability is discussed in various forms and often combined with Value Stream Mapping (VSM), a highly accepted method in practice for improving production systems using lean principles. In scientific literature, most authors present frameworks for scoring production processes (e.g. ratios, benchmarks). These approaches a...

Die Inhalte des vorliegenden Beitrags sind im Rahmen eines gemeinsamen Forschungsprojekts der Institutsbereiche Finanzwirtschaft und Controlling sowie Betriebstechnik und Systemplanung des IMW an der TU Wien mit der Magna International Europe AG und der Magna Interiors-Gruppe erarbeitet worden, wobei unser besonderer Dank den Herren Christoph Bistr...

Industry is currently undergoing a transformation towards full digitalization and intelligentization of manufacturing processes. Visionary but quite realistic concepts such as the Internet of Things, Industrial Internet, Cloud-based Manufacturing and Smart Manufacturing are drivers of the so called Fourth Industrial Revolution which is commonly ref...

Digital assistance systems (DAS) in cyber-physical assembly systems (CPAS) encounter the challenge of increasing need for transparent and personalized information that facilitates correct and efficient execution of an individual assembly task. Risks of rising physical and psychological stress triggered by constantly changing work tasks — due to lot...

Value stream mapping is a lean management method for analyzing and optimizing a series of events for production or services. Even today the first step in value stream analysis - the acquisition of the current state - is still created using pen & paper by physically visiting the production place. We capture a digital representation of how manufactur...

In den letzten Jahren ist das nationale und internationale Interesse an einem Themenkomplex der Industrie rasant gestiegen, nämlich jenem der proklamierten Vierten Industriellen Revolution – der sog. „Industrie 4.0“. So hat sich die Anzahl der Treffer für den Suchbegriff „Industrie 4.0“ auf der offenen wissenschaftlichen Suchplattform Google Sch...

Manufacturing processes have changed significantly since the early days of the steam engine and Henry Ford's assembly line. After Ford's mechanization and the first digitalization of industrial productions in the 1970s, currently a fourth industrial revolution (commonly referred to as Industry 4.0) is taking place. Industry 4.0 propagates a vision...

Der europäische Industriesektor steht derzeit vor Herausforderungen, welche vor allem durch die Globalisierung der Märkte, demographische Veränderungen sowie durch steigende Kunden- und Qualitätsansprüche und dem damit verbundene Innovationsdruck entstehen. Des Weiteren erfordert die sinkende Verfügbarkeit von Rohstoffen eine Neuausrichtung und Fle...