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Design, balancing, and sequencing are the key issues associated with assembly lines (ALs). The purpose of this paper is to identify AL design issues and to develop an integrated methodology for mixed‐model assembly line balancing (MMALB) and sequencing. Primarily, mixed‐model lines are utilized for high‐variety, low‐volume job shop or batch production. Variation of a generic product is important for the manufacturers as the demand is mostly customer driven in the present global market.

Different AL design norms, performance indexes, and AL workstation indexes have been identified in the initial stage of this work. As the paper progresses, it has focused towards an integrated approach for MMALB and sequencing addressed for small‐ and medium‐scale assembly plants. A small‐scale practical problem has been justified with this integrated methodology implemented by MATLAB.

ALs execution in the production floor require many important factors to be considered. Different line orientations, production approaches, line characteristics, performance and workstation indexes, problem definitions, balancing and product sequencing in accordance with the objective functions are needed to be taken into account by the line designer.

This paper has highlighted the important AL design characteristics and also provided an integrated approach for balancing mixed‐model assembly lines (MMALs) combined with sequencing heuristic. The findings of this paper can be helpful for the designers while designing an AL. The integrated approach for balancing and sequencing of MMALs can be used as a functional tool for assembly‐based contemporary industries.

The purpose of this paper is to introduce robust optimization approaches to balance mixed model assembly lines with uncertain task times and daily model mix changes.

Scenario planning approach is used to represent the input data uncertainty in the decision model. Two kinds of robust criteria are provided: one is min‐max related; and the other is α‐worst scenario based. Corresponding optimization models are formulated, respectively. A genetic algorithm‐based robust optimization framework is designed. Comprehensive computational experiments are done to study the effect of these robust approaches.

With min‐max related robust criteria, the solutions can provide an optimal worst‐case hedge against uncertainties without a significant sacrifice in the long‐run performance; α‐worst scenario‐based criteria can generate flexible robust solutions: through rationally tuning the value of α, the decision maker can obtain a balance between robustness and conservatism of an assembly line task elements assignment.

This paper is an attempt to robust mixed model assembly line balancing. Some more efficient and effective robust approaches – including robust criteria and optimization algorithms – may be designed in the future.

In an assembly line with significant uncertainty, the robust approaches proposed in this paper can hedge against the risk of poor system performance in bad scenarios.

Using robust optimization approaches to balance mixed model assembly line.

Various approaches and algorithms have been proposed since the 1950s to solve the assembly line (AL) balancing problem. These methods have established an AL configuration from the beginning. However, a prebalanced AL may have to be rebalanced in real life for many reasons, such as changes in the cycle time, production demand, product features or task operation times. This problem has increasingly attracted the interest of scientists in recent years. This study aims to offer a detailed review of the assembly line rebalancing problems (ALRBPs) to provide a better insight into the theoretical and practical applications of ALRBPs.

A structured database search was conducted, and 41 ALRBP papers published between 2005 and 2022 were classified based on the problem structure, objective functions, problem constraints, reasons for rebalancing, solution approaches and type of data used for solution evaluation. Finally, future research directions were identified and recommended.

Single model, straight lines with deterministic task times were the most studied type of the ALRBPs. Eighteen percent of the studies solved worker assignment problems together with ALRBP. Product demand and cycle time changes were the leading causes of the rebalancing need. Furthermore, seven future research opportunities were suggested.

Although there are many review studies on AL balancing problems, to the best of the authors’ knowledge, there have been no attempts to review the studies on ALRBPs.

Believes that an urgent need for in‐depth understanding of the relationship of staff development to education quality exists in current educational reforms, policy making, and teacher education. Based on the existing knowledge of education quality, quality management and effective schools, aims to propose a framework to show how staff development can be designed and managed to contribute to the assurance and enhancement of school education quality from the perspective of seven multimodels of school education quality. Different models emphasize different aspects of school education quality and propose different strategies to enhance it. For ensuring long‐term school education quality in a changing educational environment, staff development can be organized and managed according to the major concerns of multimodels. Proposes some practical considerations for designing and implementing school‐based staff development.

In certain manufacturing categories the type of plant layout to adopt is determined by the type of production process. However, within multi‐product mid‐volume environments the type of plant layout to select is not as obvious, with recent trends indicating that the more traditional functional layout is being replaced by a cellular approach. Aims to provide an insight into the performance of contrasting approaches to plant layout by developing generic mathematical models, based on queuing theory, to examine the limitations and ability of each layout. Subsequently optimizes the models in terms of cost, size and scheduling effectiveness, within a common framework.

This paper briefly reviews the assembly line balancing techniques developed over the last 30 years. It attempts to establish the direction of research, to identify unexplored areas with potential for study and recommends future courses of action.

The purpose of this paper is to describe a two‐level hierarchical control strategy for electrical energy transfers in multisource renewable energy systems. The aim of the control design is to perform the energy transfers, according to the sources power variations and the load characteristics.

The controller determines the operating mode of the multisource renewable energy system and the power ratio provided by each source to satisfy the load demand. The study is based on an accurate model of the DC/DC converters coupled on the DC bus. The performance of the controller is compared with the usual method based on the measurements of the system variables with sensors (solar radiation, shaft speed, voltages, and currents).

The proposed method does not need extra sensors to measure the available power for each source.

The method is developed for an hybrid system with two sources (photovoltaic and lead‐acid battery bank) and specific zero voltage switch full‐bridge isolated buck DC/DC power converters but can easily extended to more sources and other classes of DC/DC converters.

The method is assessed through computer simulations using a simple comprehensive model. An experimental device is also developed by the GREAH Research Group of University Le Havre (France). The GREAH also participates to a technologic centre with similar topology on the site of Fecamp (France).

The proposed autonomous control schema is suitable to control hybrid systems with several energy sources in remote areas.

The main contributions of this work are first to introduce a two stages controller and second to use the duty cycle value of the power converters as decision criteria to switch off/on the sources.

We present a simulation designed to capture the impact of both formal authority ties and informal socialization ties on the performance of an organization adapting to a turbulent world. We present a summary of three key models that informed our approach and then outline and describe the operation of our resulting simulation. Using an experiment that manipulated both the authority network structure and the stress the organization placed on socialization, we show inefficient authority structures harm performance, and also that socialization has a strong and nonlinear impact on peak organizational performance and on the performance of top management. We also present a case study, instantiating the general model with the specific context of a real-world organization. Finally, our integrated multimodel suggests that companies should pursue different strategies in hiring key strategic actors than they do for other actors.

The focus of preventive maintenance (PM) programmes in industry is shifting from a pure statistical basis to online condition monitoring. Examines the shortcomings of statistical‐based PM which are contributing to this shift, and the potential benefits of and current research issues within condition‐based PM. Notes that statistics and quality control techniques will continue to play a critical role in this evolution.

With hybrid simulation techniques getting popular for systems improvement in multiple fields, this study aims to provide insight on the use of hybrid simulation to assess the effect of lean manufacturing (LM) techniques on manufacturing facilities and the transition of a mass production (MP) facility to incorporating LM techniques.

In this paper, the authors apply a hybrid simulation approach to improve an educational automotive assembly line and provide guidelines for implementing different LM techniques. Specifically, the authors describe the design, development, verification and validation of a hybrid discrete-event and agent-based simulation model of a LEGO® car assembly line to analyze, improve and assess the system’s performance. The simulation approach examines the base model (MP) and an alternative scenario (just-in-time [JIT] with Heijunka).

The hybrid simulation approach effectively models the facility. The alternative simulation scenario (implementing JIT and Heijunka LM techniques) improved all examined performance metrics. In more detail, the system’s lead time was reduced by 47.37%, the throughput increased by 5.99% and the work-in-progress for workstations decreased by up to 56.73%.

This novel hybrid simulation approach provides insight and can be potentially extrapolated to model other manufacturing facilities and evaluate transition scenarios from MP to LM.