Despite extensive research on future manufacturing and the forthcoming fourth industrial revolution (implying digitalisation), there is a lack of understanding regarding specific changes that can be expected for maintenance organisations. Therefore, developing scenarios needed to define long-term strategies realisation digitalised manufacturing. This empirical Delphi-based scenario planning study first within realm, examining total 34 projections about potential internal external environment...

How do modernized maintenance operations, often referred to as "Smart Maintenance", impact the performance of manufacturing plants? The inability answer this question backed by data is a problem for industrial management, especially in light ongoing rapid transition towards an environment with pervasive digital technologies. To end, paper, which first part two-paper series, aims investigate and question, "What Smart Maintenance?". authors deployed empirical, inductive research approach...

How do modernized maintenance operations, often referred to as "Smart Maintenance", impact the performance of manufacturing plants? This question is a pressing challenge for practitioners and scholars in industrial management, direct response transition an environment with pervasive digital technologies. paper second part two-paper series. We present empirically grounded research agenda that reflects heterogeneity adoption Smart Maintenance. Focus groups interviews more than 110 experts from...

Smart manufacturing is reshaping the industry by boosting integration of information and communication technologies process. As a result, companies generate large volumes machine data which can be potentially used to make data-driven operational decisions using informative computerized algorithms. In domain, it well-known that productivity production line constrained throughput bottlenecks. The dynamics system causes bottlenecks shift among resources between runs. Therefore, prediction...

Abstract Purpose The purpose of this paper is to identify maintenance improvement potentials using an overall equipment effectiveness (OEE) assessment within the manufacturing industry. Design/methodology/approach assesses empirical OEE data gathered from 98 Swedish companies between 2006 and 2012. Further analysis Monte-Carlo simulations were performed in order study how each component impacts OEE. Findings quantifies various losses OEE, as well factors availability, utilization, speed,...

The advancements in machine learning (ML) techniques open new opportunities for analysing production system dynamics and augmenting the domain expert's decision-making. A common problem experts on shop floor is detecting throughput bottlenecks, as they constrain throughput. Detecting bottlenecks necessary to prioritise maintenance improvement actions obtain greater existing literature provides many ways detect from data, using statistical-based approaches. These approaches can be best...

To support manufacturing firms in realising the value of Artificial Intelligence (AI), we embarked on a six-year process research and practice to enhance popular widely used CRISP-DM methodology. We extend into continuous, active, iterative life-cycle AI solutions by adding phase 'Operation Maintenance' as well embedding task-based framework for linking tasks skills. Our key findings relate difficult trade-offs hidden costs operating maintaining managing drift, ensuring presence domain, data...

Recent development in the predictive maintenance field has focused on incorporating artificial intelligence techniques monitoring and prognostics of machine health. The current applications manufacturing are now more dependent data-driven Machine Learning algorithms requiring an intelligent effective analysis a large amount historical real-time data coming from multiple streams (sensors computer systems) across machines. Therefore, this article addresses issues pre-processing that have...

Identifying, and eventually eliminating throughput bottlenecks, is a key means to increase productivity in production systems. In the real world, however, bottlenecks challenge. This due landscape of complex factory dynamics, with several hundred machines operating at any given time. Academic researchers have tried develop tools help identify eliminate bottlenecks. Historically, research efforts focused on developing analytical discrete event simulation modelling approaches However, rise...

Manufacturing companies struggle to be efficient and effective when conducting root cause analyses of production disturbances; a fact which hinders them from creating developing resilient systems. This article aims describe the challenges enablers identified in current research relating different phases analysis. A systematic literature review was conducted, total 14 17 are described. These correlate Examples "need for expertise", "employee bias", "poor data quality" "lack integration",...

Industry increasingly focuses on data-driven digital twins of production lines, especially for planning, controlling and optimising applications. However, the lack open data manufacturing systems presents a challenge to development new strategies. To fill this gap, paper aim introduce strategy generating random lines simulating their behaviour, thus enabling generation synthetic data. So far, such can be recorded in event logs or machine status format, with latter adopted use cases. do so,...

Abstract Manufacturing companies continuously capture shop floor information using sensors technologies, Execution Systems (MES), Enterprise Resource Planning systems. The volumes of data collected by these technologies are growing and the pace that growth is accelerating. constantly changing but immediately relevant. Collecting analysing them on a real-time basis can lead to increased productivity. Particularly, prioritising improvement activities such as cycle time improvement, setup...

Purpose A common understanding of what events to regard as production disturbances (PD) are essential for effective handling PDs. Therefore, the purpose this paper is answer two questions: how individuals with or maintenance management positions in industry classifying different PD factors? Which factors being measured and registered PDs companies monitoring systems? Design/methodology/approach longitudinal approach using a repeated cross-sectional survey design was adopted. Empirical data...

Data-driven decision support for maintenance management is necessary modern digitalized production systems. The data-driven approach enables analyzing the dynamic system in real-time. Common problems within are that decisions experience-driven, narrow-focussed and static. Specifically, machine criticality assessment a tool used manufacturing companies to plan prioritize activities. well exemplified by this industrial practice. not trustworthy, seldom updated focuses on individual machines....

Innovations and advancements in technology create new opportunities to run maintain manufacturing plants, which we refer as digitalised manufacturing. This development is recognised a socio-technical system (STS) change, where change the production system's goals, technology, processes, people, or environment may lead ripple effects between those sub-systems. Despite this, use cases account for most of research within manufacturing, while little attention has been devoted leadership...

Discrete event simulation (DES) projects rely heavily on high input data quality. Therefore, the management process is very important and, thus, consumes an extensive amount of time. To secure quality and increase rapidity in DES projects, there are well structured methodologies to follow, but a detailed guideline for how perform crucial handling data, missing. This paper presents such methodology, including description 13 activities their internal connections. Having this kind methodology...

Discrete event simulation (DES) projects rely heavily on high input data quality. Therefore, the management process is very important and, thus, consumes an extensive amount of time. To secure quality and increase rapidity in DES projects, there are well structured methodologies to follow, but a detailed guideline for how perform crucial handling data, missing. This paper presents such methodology, including description 13 activities their internal connections. Having this kind methodology...

A sustainable manufacturing systems design using processes, methodologies, and technologies that are energy efficient environmental friendly is desirable essential for development of products services. Efforts must be made to create maintain such systems. Discrete Event Simulation (DES) in combination with Life Cycle Assessment (LCA) system can utilized evaluate a performance taking into account measures before actual construction or use the system. In this paper, we present case study show...

The digital transformation of manufacturing industries is expected to yield increased productivity. Companies collect large volumes real-time machine data and are seeking new ways use it in furthering data-driven decision making. A challenge for these companies identifying throughput bottlenecks using the they collect. This paper proposes a algorithm better identify bottleneck groups provide diagnostic insights. based on active period theory analysis. It integrates available execution...

Operators remain as important resources in complex final assembly. To sustain a multi-variant production, it is necessary for operators to manage high demands from cognitive workload perspective. In such situations, work instructions can support cognitively. However, are often insufficient or unused this paper, results testbed experiments presented where assembly was supported by different types of with differing information content. Results indicate that operator performance terms perceived...

Digitalisation is argued to increase the efficiency of maintenance activities in a production system. One consequence digitalisation data deluge; this allows analytics methods and technologies be used. However, actual analytical used may differ, thus leading many scientific papers on topic. The purpose our contribution find cluster regarding implemented approaches relevant for use maintenance. Our research based broad, systematic literature review consisting two-step search approach combined...

High-quality input data are a necessity for successful discrete event simulation (DES) applications, and there available methodologies collection in DES projects. However, contrast to standalone projects, using as daily manufacturing engineering tool requires high-quality production be constantly available. In fact, has been major shift the application of from system design operations, accompanied by stream research on automation management interoperability between sources models....

Purpose The purpose of this paper is to increase productivity through smart maintenance planning by including as one the objectives organization. Therefore, goals are investigate existing machine criticality assessment and identify components tool productivity. Design/methodology/approach An embedded multiple case study research design was adopted in paper. Six different cases were chosen from six production sites operated three multi-national manufacturing companies. Data collection carried...

Purpose Scholars and practitioners within industrial maintenance management are focused on understanding antecedents, correlates consequences of the concept “Smart Maintenance,” which consists four dimensions, namely, data-driven decision-making, human capital resource, internal integration external integration. In order to facilitate this understanding, valid reliable empirical measures need be developed. Therefore, paper aims develop a psychometric instrument that dimensions Smart...