Work allocation strategies for serial assembly lines under high labour turnover

Labour turnover can be very detrimental to the performance of traditional serial assembly lines. It has been shown that high turnover rates can reduce annual production throughput in serial assembly lines by more than 16% when these lines operate under a balanced work allocation strategy. This paper investigates whether alternative production methods, such as Bucket Brigades, can out-perform traditional lines by utilizing dynamic work allocation and active operator replacement policies in order to absorb better the variability introduced by labour turnover. The study performed was divided into two phases. Phase I consisted of using a simple three-station linear assembly line to compare the performance of the Bucket Brigades method against a traditional line (fixed work allocation, static operator replacement), and a method using fixed work allocation along with a dynamic replacement policy. In Phase II, a six-station serial assembly line was used to compare the performance of Bucket Brigades against the traditional balanced line method. The analyses were based on simulation models that used monthly turnover rates of 0, 6 and 12%. Phase I showed that the Bucket Brigade method outperformed the other two methods consistently when operating under moderate (6%) and high (12%) turnover rates. Phase II demonstrated that the Bucket Brigade method was better than the traditional production method in every instance, including the case with 0% turnover.     

Performance of serial assembly line designs under unequal operator speeds and learning

The traditional balanced assembly line designs can perform quite inefficiently under the presence of high labor turnover, low operator learning rates, and stochastic processing times. In these situations assembly line designs based on dynamic work allocation and work sharing principles have been shown to render a higher and less variable throughput. However, for situations where low labor turnover conditions and high operator learning rates exist, the traditional balanced lines still tend to be most productive. This paper has two objectives: to introduce a method based on work sharing principles, which we denominate Modified Work Sharing (MWS), and to develop some simple analytical tools that will allow us to compare the performance of this method with the traditional and other dynamic work allocation line designs. These results suggest that the traditional method is the most affected by the introduction of new operators in the production lines and thus the most affected by variability in general. On the other hand, dynamic work allocation methods appear to better absorb the variability introduced by new operators by sharing the workload of new operators with the more experienced members of the line.     

Operator allocation planning for reconfigurable production line in one-of-a-kind production

In a one-of-a-kind production (OKP) company, the operation routing and processing time of an order are usually different from the others due to high customisation. As a result, an OKP company needs to dynamically adjust the production resources to keep the production lines reconfigurable. Through a proper assignment of operators in different sections of a production line, bottlenecks and operator re-allocation during production can be reduced effectively. In this paper, a mathematical model is introduced for optimal operator allocation planning on a reconfigurable production line in OKP. The optimisation objectives are to minimise the total number of the operators, total job earliness and tardiness, and the average work-in-process storage. A branch-and-bound algorithm with efficient pruning strategies is developed to solve this problem. The proposed model and the algorithm are empirically validated by using the data of a windows and doors manufacturing company. A software system based on the proposed approach has been implemented in the company.     

Learning and labour assignment in a dual resource constrained cellular shop

Recent studies have shown that in a cellular shop that benefits from learning due to repetitive processing, limitations attributable to routing flexibility can be more than offset. Moreover, the shop can respond more quickly to changes in demand than a job shop. This study examines the impact of labour assignments in a dual constrained cellular shop in which processing times decrease with operator task repetition. Results indicate that in the presence of operator learning, shop performance is significantly affected by the flexibility permitted in labour assignments. Moreover, the sensitivity of performance to labour assignments is significantly impacted by staffing levels and the magnitude of learning effects.     

Workforce planning and allocation for mid-volume truck manufacturing: A case study

A case study for the short-term workforce planning and allocation for labour-intensive transfer lines is addressed. Trucks are assembled on a serial line, and they show large differences in the processing times at each station. These differences are due to the assembling options provided to the customers. Given the assignment of operations to stations, we have to find a loading sequence for the products, a worker allocation and a floater time allocation to minimize the whole labour costs at the line. We develop a solution approach for this problem and, in particular, discuss the necessities and implications by considering a rolling planning horizon. Especially, when planning for a number of subsequent shifts, we have to model the time interdependencies carefully. The results of the numerical studies show that relevant savings can be achieved by using an advanced planning system.     

Due-date assignment scheduling involving job-dependent learning effects and convex resource allocation

ABSTRACT

This article addresses single machine resource allocation scheduling problems with learning effects, where learning effects mean job-dependent position-based learning effects. For the common due-date assignment (CON) and slack due-date assignment (SLK) methods, a bi-cost analysis of the scheduling cost and the total weighted resource consumption cost is provided. The objective is to determine the optimal job sequence and the resource allocation simultaneously, such that the scheduling cost (the total weighted resource consumption cost) is minimized subject to the total weighted resource consumption cost (the scheduling cost) being limited. Solution procedures are provided for the problems under consideration.     

A flexible labour division approach to the polygon packing problem based on space allocation

This paper deals with the two-dimensional satellite module polygon packing problem. Based on the duality of material and space, it regards the polygon packing problem as a space allocation problem, which involves allocating the container space to the given polygons reasonably and efficiently. Ant colony’s labour division is essentially a kind of task allocation. Using this task allocation to achieve the space allocation in polygon packing problems, a flexible labour division approach (FLD) is proposed based on the response threshold model. According to the characteristics of space allocation in polygon packing problems, FLD designs three actions for polygons to occupy the container space. With the interaction between environmental stimulus and response threshold, each polygon takes an appropriate action to complete the space allocation and a layout that meets the requirements of satellite module layout is obtained. The results of standard test instances demonstrate the effectiveness of FLD when compared with self-organisation emergence algorithm. Moreover, experiments on the general polygon packing problem also show that FLD is competitive with other existing algorithms.     

Labour mobility and the optimal wage differential: Labour allocation as a disequilibrium process†

Any study of labour allocation must take into account the fact that the industria structure of the economy is bound to change over time and that, this will put pressure on each kind of labour to redistribute itself continuously. Differing rates of labour-saving technical progress will have the same effect. Since labour is hardly perfectly mobile, this implies that its allocation should be regarded as essentially a disequilibrium process and that dynamic criteria should replace the usual comparative static criteria of efficiency. The purpose of this paper is to outline such a treatment.

The analysis has deliberately been conducted at a relatively high level of abstraction because even a simple theoretical framework seemed to be lacking. The most important empirical feature that needs to be supplied is of course the labour mobility function. It may well be found that neither of the two cases distinguished in the paper corresponds satisfactorily to what is actually observed. Two well-known studies by Reddaway (1959) and de Wolff (1965) go so far as to suggest that firms may in practice increase or reduce their labour forces without altering their wage rates from the prevailing market levels. Whether such behaviour is optimal or not cannot be determined without bringing detailed institutional evidence to bear, but it does at any rate point, to the possibility that the mobility function may be shifted upwards or downwards according to whether the firm is active or passive in, its recruitment of labour.     

A heuristic for solving the redundancy allocation problem for multi-state series-parallel systems

The redundancy allocation problem is formulated with the objective of minimizing design cost, when the system exhibits a multi-state reliability behavior, given system-level performance constraints. When the multi-state nature of the system is considered, traditional solution methodologies are no longer valid. This study considers a multi-state series-parallel system (MSPS) with capacitated binary components that can provide different multi-state system performance levels. The different demand levels, which must be supplied during the system-operating period, result in the multi-state nature of the system. The new solution methodology offers several distinct benefits compared to traditional formulations of the MSPS redundancy allocation problem. For some systems, recognizing that different component versions yield different system performance is critical so that the overall system reliability estimation and associated design models the true system reliability behavior more realistically. The MSPS design problem, solved in this study, has been previously analyzed using genetic algorithms (GAs) and the universal generating function. The specific problem being addressed is one where there are multiple component choices, but once a component selection is made, only the same component type can be used to provide redundancy. This is the first time that the MSPS design problem has been addressed without using GAs. The heuristic offers more efficient and straightforward analyses. Solutions to three different problem types are obtained illustrating the simplicity and ease of application of the heuristic without compromising the intended optimization needs.     

Customer segmentation,allocation planning and order promising in make-to-stock production

Modern advanced planning systems offer the technical prerequisites for an allocation of “available-to-promise” (ATP) quantities—i.e. not yet reserved stock and planned production quantities—to different customer segments and for a real time promising of incoming customer orders (ATP consumption) respecting allocated quota. The basic idea of ATP allocation is to increase revenues by means of customer segmentation, as it has successfully been practiced in the airline industry. However, as far as manufacturing industries and make-to-stock production are concerned, it is unclear, whether, when, why and how much benefits actually arise. Using practical data of the lighting industry as an example, this paper reveals such potential benefits. Furthermore, it shows how the current practice of rule-based allocation and consumption can be improved by means of up-to-date demand information and changed customer segmentation. Deterministic linear programming models for ATP allocation and ATP consumption are proposed. Their application is tested in simulation runs using the lighting data. The results are compared with conventional real time order promising with(out) customer segmentation and with batch assignment of customer orders. This research shows that—also in make-to-stock manufacturing industries—customer segmentation can indeed improve profits substantially if customer heterogeneity is high enough and reliable information about ATP supply and customer demand is available. Surprisingly, the choice of an appropriate number of priority classes appears more important than the selection of the ATP consumption policy or the clustering method to be applied.     

A cloud-based intelligent decision-making system for order tracking and allocation in apparel manufacturing

This paper addressed the order tracking and allocation problem in an apparel manufacturing environment with multiple plants. A cloud-based intelligent decision-making system was developed to tackle this problem, which combined radio frequency identification and cloud computing technologies to capture real-time production records and make remote production order tracking, and employed computational intelligence techniques to generate effective order allocation solutions to appropriate plants. To evaluate the effectiveness of the proposed system, the system was implemented in an apparel manufacturing company with multiple plants, which reported distinct reductions in production costs and increases in production efficiency. This paper also investigated learning phenomenon in production and its effects on production efficiency and decision-making performance.     

Who creates jobs? Venture capital,research grants,and regional employment in the U.S.

We build on the exploratory and exploitative learning literature that suggests that venture capital and governmental research grants may impact regional employment in a different manner. Using a regional employment dataset in the U.S. (United States) medical device sector, our analysis reveals that research grants contribute to create a greater level of regional employment compared with venture capital funding. Furthermore, the positive effects of both funding sources are more salient when intellectual capital is abundant in the region. More specifically, the interaction effect of research grants and intellectual capital is gradually increased in the long term and eventually becomes greater than that of venture capital and intellectual capital, which is relatively constant. These findings highlight the heterogeneous motivations and consequences of two funding sources that should be considered in the future resource allocation policy accordingly.     

On the who-rule in Dual Resource Constrained (DRC) manufacturing systems

The who-rule is a labour allocation rule used in labour and machine-limited dual resource constrained (DRC) systems. A who-rule selects one worker out of several workers to be transferred to a work centre. By means of a practical instance, the paper shows that the who-rule plays a role in the daily practice of worker assignment. Previous simulation studies, however, either have not mentioned the who-rule or have treated it as a fixed factor. The present study will explore the need of including the who-rule in simulation studies. It will describe in detail at what decision moments the who-rule needs to be applied in simulation. Further, it will explore the flow time effects of applying different who-rules in several DRC systems where labour flexibility is limited and workers differ with respect to task proficiencies, the number of skills they possess and the loads of work centres for which they are responsible. As with other labour allocation rules, the impact of the who-rule depends on the specific DRC shop modelled. The paper will show that the average labour utilization, and the types and extent of worker differences, determine the impact of the who-rule on shop performance.     

Dynamic allocation of communicating tasks in computational grids

This paper studies task allocation in computational grids operating in a dynamic and uncertain environment. Computational grids consist of loosely coupled heterogeneous resources or agents with finite buffer capacities. These grids are primarily used to process large-scale applications consisting of several interdependent tasks. The task allocation problem is modeled as an infinite horizon Markov decision process, with the resource service times and the task arrivals following general probability distributions. We explicitly consider the communication cost between agents incurred in coordinating the execution of interdependent tasks. We show that a stationary optimal policy exists for this task allocation problem. Furthermore, we develop an action elimination procedure for reducing the complexity of computational methods in finding the optimal policy. We also present a real-time heuristic policy based on certain structural properties of the problem. Finally, computational results are presented that compare the performance of the heuristic policy with respect to other approaches for allocating tasks in the grid. Results from this paper are also applicable to the task allocation problem in manufacturing and service areas such as distributed design, project management and supplier coalitions.     

Human–machine function allocation: a functional modelling approach

Function allocation between humans and systems is an important factor regarding safety, reliability and efficiency of industrial processes. One should allocate functions in order to maximise the operator's situation understanding and ability to handle unexpected events. Functional models can be used to study function allocation in a process control environment, because they explicitly describe functions and tasks of both the plant and the operator. The Halden Reactor Project is currently engaged in such a project called function allocation methods (FAME), aimed specifically at the work in a nuclear power plant control room. This paper describes the main features of the approach, and discusses how functional modelling can be used to address the issue of how much information is necessary for the operator, and thereby give a basis for how functions should be allocated.     

A Multi‐attribute Reliability Allocation Method Considering Uncertain Preferences

In reliability allocation, certain reliability values are assigned to subsystems and components to achieve the required system reliability. One big challenge in solving such reliability‐based design problems is how to handle the uncertain preferences of a decision maker on multiple attributes of interest. In this paper, we propose a new ordered weighted averaging (OWA) method based on an analytic hierarchy process to address the decision maker's uncertain preferences in reliability allocation. In the proposed OWA operator, a bi‐objective mathematical programming model considering both maximal entropy and minimal variance is transformed into a single‐objective mathematical programming model using an ideal‐point method. The maximum entropy minimal variance OWA operator takes full advantage of available information and avoids overestimating the decision maker's preferences. A detailed computational procedure is presented to facilitate the implementation of the proposed method in practice. An illustrative example about the powertrain of fuel cell vehicles is provided to demonstrate the effectiveness of this method in handling multiple attributes with uncertain preferences in reliability allocation. Copyright © 2015 John Wiley & Sons, Ltd.     

The impact of dwell point policy in an Automated Storage/Retrieval System

Automated storage and retrieval systems (AS/RS) are devices that allow intensive storage of materials. They can improve the supply chain performance, assuring more available volume for storage, lower labour costs and higher handling throughput of warehousing. Furthermore, the automated control allows the probability of errors in storage and retrieval to be minimised, along with the probability of product damage during movements. The purpose of the paper is to find the best solution in order to find the optimal dwell point policy, among different rules, able to minimise the travel time and distance travelled by stacker cranes, and consequently warehousing costs. An original and innovative model was developed in order to investigate the dwell point position for random allocation of unit loads. A software platform was developed to validate the proposed model by computer simulations. The performance of the system was analysed in a parametric/continuous way, varying at the same time the number of spans and levels, the height of the input/output point and the interval between requested missions. The results show that the developed model allowed convenience areas to be identified among the policies in which the travel time, distance travelled, and consequently warehousing costs are minimised, by varying different parameters.     

A bi-objective robust model for emergency resource allocation under uncertainty

Emergency resource allocation constitutes one of the most critical elements of response operations in the field of emergency management. This paper addresses an emergency resource allocation problem which involves multiple competing affected areas and one relief resource centre under supply shortage and uncertainty in the post-disaster phase. In humanitarian situations, both the efficiency and fairness of an allocation policy have a considerable influence on the effectiveness of emergency response operations. Thus, we formulate a bi-objective robust emergency resource allocation (BRERA) model which tries to maximise efficiency as well as fairness under different sources of uncertainties. To obtain decision-makers’ most preferred allocation policy, we propose a novel emergency resource allocation decision method which consists of three steps: (1) develop a bi-objective heuristic particle swarm optimisation algorithm to search the Pareto frontier of the BRERA model; (2) select a coefficient to measure fairness; and (3) establish a decision method based on decision-makers’ preference restricted by the fairness coefficient. Finally, a real case study taken from the 5 December 2008 Wenchuan Earthquake demonstrates the effectiveness of the proposed method through numerical results. The solution and model robustness are also analysed.     

自适应分数阶算子的图像增强

为了突出图像纹理细节的同时保留平滑区域,节省确定分数阶微分阶次的时间,提出了一种改进的自适应分数阶微分算子。首先将经典Tiansi模板分解为四个不同方向,分别与待处理像素点进行卷积,达到增强图像纹理细节的效果;其次针对Tiansi算子需通过多次实验确定最佳微分阶次的现状,结合图像的局部特征信息,构建了具有自适应能力的分数阶阶次模型,能够获得比原图像更丰富的细节信息。对多组不同场景图像的实验结果表明：构建的自适应分数阶微分算子有效地增强了图像的纹理细节,自适应分数阶微分算子的主观视觉效果和客观评价指标均优于原图像,其客观评价指标中的平均梯度、信息熵、对比度相比原图像平均提高190.3%、8.1%、18.3%;平均梯度、对比度相比Tiansi算子处理后的图像平均提高45.0%、9.6%。     

Reactive power transfer allocation method with the application of artificial neural network

A novel method to identify the reactive power transfer between generators and load using modified nodal equations is proposed. On the basis of the solved load flow results, the method partitions the Y-bus matrix to decompose the current of the load buses as a function of the generators' current and voltage. Then it uses the load voltages from the load flow results and decomposed load currents to determine reactive power contribution from each generator to loads. The validation of the proposed methodology is demonstrated by using a simple 3-bus system and the 25-bus equivalent system of south Malaysia. Next part here focuses on creating an appropriate artificial neural network (ANN) to solve the same problem in a simpler and faster manner. The basic idea is to use supervised learning paradigm to train the ANN. Most commonly used feedforward architecture has been chosen for the proposed ANN reactive power transfer allocation technique. Almost all system variables obtained from load flow solutions are utilised as an input to the neural network. Moreover, tan-sigmoid activation functions are incorporated in the hidden layer to realise the nonlinear nature of the reactive power transfer allocation. The targets of the ANN corresponding to the previously developed reactive power transfer allocation method. The 25-bus equivalent system of south Malaysia is utilised as a test system to illustrate the effectiveness of the ANN output compared with that of the modified nodal equations method. The ANN output provides promising results in terms of accuracy and computation time.