Old machine reconditioning projects extend the life length of machines with reduced investments, however they frequently involve complex challenges. Due to lack technical documentation and fact that are running in production, can require a reverse engineering phase extremely short commissioning times. Recently, emulation software has become key tool create Digital Twins carry out virtual new manufacturing systems, reducing time increasing its final quality. This paper presents an industrial...

In light of the Industry 5.0 trend towards human-centric and resilient industries, human-robot collaboration (HRC) assembly lines can be used to enhance productivity workers’ well-being, provided that optimal allocation tasks available resources determined. This study investigates line balancing problem (ALBP), considering HRC. problem, abbreviated ALBP-HRC, arises in advanced manufacturing systems, where humans collaborative robots share same workplace simultaneously perform parallel or...

The new industrial revolution brings important changes to organizations that will need adapt their machines, systems and employees’ competences sustain business in a highly competitive market. Management philosophies such as lean also the improvement possibilities Industry 4.0 brings. This paper presents review on role of simulation context 4.0. Additionally, conceptual framework where optimization make approach more efficient, speeding up system improvements reconfiguration, by means an...

Digitalization through Industry 4.0 technologies is one of the essential steps for complete collaboration, communication, and integration heterogeneous resources in a manufacturing organization towards improving performance. One ways to measure effective utilization critical resources, also known as bottlenecks. Finding such system has been significant focus research several decades. However, finding bottleneck complex difficult due interdependencies interactions many resources. In this...

The improvement of emergency department processes involves the need to take into consideration multiple variables and objectives in a highly dynamic unpredictable environment, which makes decision-making task extremely challenging. use different methodologies tools support process is therefore key issue. This article presents novel approach healthcare Discrete Event Simulation, Simulation-Based Multi-Objective Optimization Data Mining techniques are used combination. methodology has been...

Data-driven simulation (DDS) is fundamental to analytical and decision-support technologies in Industry 4.0 smart manufacturing. This study investigates the potential of DDS for resource allocation (RA) high-mix, low-volume manufacturing systems with mixed automation levels. A DDS-based decision support system (DDS-DSS) developed by incorporating two RA strategies: simulation-based bottleneck analysis (SB-BA) multi-objective optimization (SB-MOO). To enhance performance SB-MOO, a unique...

In line with Industry 5.0, ergonomic factors have recently received more attention in balancing assembly lines to enhance the human-centric aspect. Meanwhile, today's mass-customized trend yields manufacturers offset for different product variants. Thus, this study addresses mixed-model problem (MMALBP) by considering worker posture. Digital human modeling and posture assessment technologies are utilized assess risks of work-related musculoskeletal disorders using a method known as rapid...

The recent Industry 4.0 trend, followed by the technological advancement of collaborative robots, has urged many industries to shift towards new types assembly lines with human-robot collaboration (HRC). This type manufacturing line, in which human skill is supported robot agility, demands an integrated balancing and scheduling tasks operators among stations. study attempts deal these joint problems straight U-shaped while considering different objectives, namely, number stations (Type-1),...

Purpose The positioning of the customer order decoupling point (CODP) is an important strategic consideration for supply chains. Recently, research has focused only on static effects CODP positioning. purpose this paper to expand body knowledge by describing dynamic consequences that arise from shifting upstream or downstream. Design/methodology/approach A generic assembly‐to‐order system dynamics simulation model developed and used evaluate CODP. Findings Placing downstream allows...

Multi-objective evolutionary algorithms (MOEAs) are often criticized for their high-computational costs. This becomes especially relevant in simulation-based optimization where the objectives lack a closed form and expensive to evaluate. Over years, meta-modeling or surrogate modeling techniques have been used build inexpensive approximations of objective functions which reduce overall number function evaluations (simulations). Some recent studies however, pointed out that accurate models...

Abstract Reacting quickly to changing market demands and new variants by improving adapting industrial systems is an important business advantage. Changes are costly; especially when those already in place. Resources invested should be targeted so that the results of improvements maximized. One method allowing this combination discrete event simulation, aggregated models, multi-objective optimization, data-mining shown article. A real-world optimization case study problem conducted resulting...

Purpose This study aims to propose an efficient optimization algorithm solve the assembly line balancing problem (ALBP). The ALBP arises in high-volume, lean production systems when decision-makers aim design while satisfying a set of constraints. Design/methodology/approach An improved genetic (IGA) is proposed this deal with optimize number stations and workload smoothness. Findings To evaluate performance IGA, it used well-known benchmark problems real-life faced by automobile...

While day-to-day questions come with a variety of answer types, the current question-answering (QA) literature has failed to adequately address diversity questions. To this end, we present GooAQ, large-scale dataset types. This contains over 5 million and 3 answers collected from Google. GooAQ are semi-automatically Google search engine using its autocomplete feature. results in naturalistic practical interest that nonetheless short expressed simple language. mined Google's responses our...

Multi-objective optimisation (MOO) is a powerful approach for generating set of optimal trade-off (Pareto) design alternatives that the decision-maker can evaluate and then choose most-suitable configuration, based on some high-level strategic information. Nevertheless, in practice, choosing among large number solutions Pareto front often daunting task, if proper analysis visualisation techniques are not applied. Recent research advancements have shown advantages using data mining to...

The current work presents a decision support system architecture for evaluating the features representing health status to predict maintenance actions and remaning useful life of component. evaluation is possible through pattern analysis past measurements focused research components. Data mining visualization tools help in creating most suitable patterns learning insights from them. Estimations like split values or measurement frequency component achieved classification methods data mining....