Manufacturing industries struggle to devise precise planning and scheduling solutions due to unpredictable business situations. Additionally, uncertainties in production such as machine breakdowns, labour absenteeism, cycle time deviations, etc., would further deteriorate production plans and lead to uncertainty in decision-making processes. Flow shops with bottlenecks are particularly susceptible to these disturbances. Moreover, the random variations in cycle time variations can cause the bottleneck to shift between different stages. Literature indicates that conventional job release methods are ineffective in addressing these difficulties. In contrast, workload control methods would provide better solutions. Hence, a flow shop model has been developed and simulated using the variables like process time variations and bottleneck shifting on the discrete-event simulation software. The flow shop model incorporates realistic shop characteristics which are subjected to random process time variations, so as to assess the performance. The outcomes of the experimentation demonstrate that order release methods play a pivotal role in improving the performance of flow shops in more volatile situations.

The rotor blade manufacturing industry struggles to devise precise planning and scheduling approaches due to uncertainties in production situations. Bottleneck workloads, process time variations and re-entrant flows with varied arrival frequencies would interrupt production schedules and adversely affect the shop’s performance. Hence, an attempt has been made to study the significant impact of disproportionate workloads and the influence of innovative order release methods integrated with capacity adjustment features to enhance performance. The rotor blade manufacturing process has been thoroughly observed to incorporate the uncertain events that cause disturbance in production. A simulation model was created on a discrete event simulation platform incorporating problem phenomena through the conceptualization phase. The randomness present in the process was assessed using an input modelling approach which has resulted in probabilistic equations. The model has been verified and validated to ensure accuracy and was then subjected to 576 experimentations representing different scenarios that occur in a flow shop. Relevant workload control policies are executed to judge their effectiveness followed by Analysis of Variance Techniques. In addition, order release methods were ranked with the help of Tukey’s tests for contribution computation. Outcomes of experimentations revealed that order release methods have a major share of 80.2 percent to the throughput and 42.84 percent to flow time performance indicating the benefits of workload control strategies in decision-making during uncertain situations.

The re-entrant flow with an unpredictable nature of arrival would apparently harm production plans and schedules in flow type of shops. The re-entrant flow with varied arrival frequencies in rotor blade manufacturing is quite complicated and results in disproportionate workloads. Hence, an attempt has been made to study the significant influence of disproportionate workloads and research on an innovative order release method to enhance performance. The manufacturing process was observed thoroughly to incorporate the uncertain events that cause disturbance in the production. A simulation model was developed on a discrete event simulation platform by analysing problem phenomena right from the conceptualization phase. The model has been verified and validated to ensure the accuracy. The model was subjected to 288 experiments representing different scenarios that a flow shop undergoes in reality. The factors considered in the experimentation were re-entrant frequency, re-entrant proportions, order release methods and priority dispatching rules. A refined load release policy for disproportionate loads has been proposed to judge its effectiveness in terms of profit computation by comparing it with other relevant policies. Results of the experiment revealed that the order release methods contribute 95.93% to throughput performance, in addition, the use of the new re-entrant method policy in the above scenario was productive in improving the overall shop performance.

Advances in information technology and increased social networking have increased health awareness among people in this era. The increased health awareness has prompted people to eat healthy and stay fit. In this regard, the food sector has seen tremendous demand in terms of good quality vegetables/fruits, cereals, with hygiene, nutrition, proteins etc. With the consumer willing to pay an extra premium for the quality expected, it has been observed that the producers are still offered low prices for a good quality produce whereas the intermediaries grab a huge share of the price paid by the consumer. This research tried to understand the supply chain with the farmers in focus and explored the influence of farmer demographics and the supply chain issues on the performance of the organized retail. Linear regression analysis was used to test the linear relationship of supply chain issues with organized retailer performance. The outcome of the study implies that independent variables like demographic characteristics and supply chain issues had no control over the retailer’s performance.

The Garment manufacturing industry is facing several challenges in meeting its customer requirements due to uncertainties associated with production. Varieties of products that include many components to be produced on different machines having variations in terms of due dates and labour productivity which would make the job shop complicated for scheduling. Hence, an investigation is necessary to evaluate the influence of above underlying factors on the shop’s performance. The conceptual model was initially developed, that represents the problem entity followed by the development of a simulation model on a discrete event simulation platform. The resource capacity, process timings and other related data required for feeding the model were collected through process observation techniques. The model was then validated by conducting sensitivity analysis for evaluating the model structure, logic, and causal relationships. Artificial scenarios were generated to experiment with the model performance that mimics real time situations in terms of varying the fill rate and workload norms at distinct levels. Effectiveness of order release policies and priority dispatching rules were monitored by conducting 90 experiments determined through design of experiments. Influence of the workload control methods were evaluated through Analysis of Variance techniques to understand the percentage contribution of each variable on performance. The influence of these variables on different output measures was evaluated through Tukey tests. The experimentation revealed that flowtime is influenced to the extent of 59.72 percent by workload norms and order release methods have 59.2 percent influence on throughput.

Electric vehicle battery enclosure systems under vibrational loading may experience structural damage, reducing the lifespan of lithium-ion cells. Honeycomb sandwich structures are widely used in EV battery systems due to their high stiffness-to-weight ratio and superior vibration performance. The present study is undertaken to investigate the dynamic behaviour of honeycomb sandwich panels using ANSYS Workbench. A three-dimensional model of a sandwich structure consisting of an aluminium core and composite face sheets is developed in ANSYS. Modal analysis and power spectral density-based random vibration analysis are performed to examine the impact of face-sheet thickness (0.5–2.5 mm) and layup configuration on structural performance. The modal analysis reveals that the natural frequencies increase considerably with thickness up to 1.5 mm due to increased bending stiffness. The results of random vibration analysis demonstrate a substantial reduction in total deformation and equivalent stress with increasing thickness. Among the configurations studied, the [0C/0G]/Core/[0G/0C] layup demonstrates the most favourable response under the present PSD loading condition due to fibre alignment with the principal loading direction. The findings are further converted into practical design guidelines for electric vehicle battery enclosures, including an appropriate face-sheet thickness range of 1.0–1.5 mm and fibre orientations aligned with the principal loading direction, while considering the associated mass penalty. These findings provide a design-oriented framework for selecting thickness and layup configuration to achieve a practical balance between vibration resistance and weight.