Maximizing Throughput of Bucket Brigades on Discrete Work Stations

One way to coordinate workers along an assembly line that has fewer workers than work stations is to form a bucket brigade. The throughput of a bucket brigade on discrete work stations may be compromised due to blocking even if workers are sequenced from slowest to fastest. For a given work distribution on the stations we find policies that maximize the throughput of the line. When workers have very different production rates, fully cross‐training the workers and sequencing them from slowest to fastest is almost always the best policy. This policy outperforms other policies for most work distributions except for some cases in which limiting the work zones of workers produces higher throughput. In environments where the work can be adjusted across stations, we identify conditions for a line to prevent blocking.     

Impact of Storage Assignment Decisions on a Bucket Brigade Order Picking Line

Bucket brigade order picking is a method for retrieving orders from a storage rack where workers follow a fixed sequence and dynamically adjust to variability in work content along the rack. The method is simple and has been shown to provide superior performance in many applications. In this article, we analyze how the location in which products are stored in the rack affects throughput. We identify conditions where storage decisions have a large impact on throughput (e.g., a 20% increase in productivity) and conditions where the impact is minimal. Conditions associated with high impact are high variation in worker skill, high variation in SKU volume, and a moderate level of walking‐to‐picking work content per pick list.     

Performance of Cellular Bucket Brigades with Hand‐Off Times

A cellular bucket brigade is a way to coordinate workers along an aisle with work content on both sides. Each worker in a cellular bucket brigade works on one side of the aisle when he proceeds in one direction, and he works on the other side when he proceeds in the reverse direction. Although the cellular bucket brigade eliminates the unproductive walk‐back, it requires more hand‐offs to assemble a product than a traditional (serial) bucket brigade. These hand‐offs may waste significant production capacity as each of them requires an exchange of work, which can be complicated and time‐consuming in practice. This motivates us to investigate the impact of hand‐off times on the cellular bucket brigade's performance. We identify sufficient conditions to ensure no workers are idle in the long run and for the system to self‐balance in a model with hand‐off times. Our results suggest that even with significant hand‐off times, the cellular bucket brigade can remain substantially (about 50%) more productive than the traditional bucket brigade especially if the team size is small and the workers’ work velocities are close to their walk velocity.     

Cross‐Training with Imperfect Training Schemes

Cross‐training workers is one of the most efficient ways of achieving flexibility in manufacturing and service systems for increasing responsiveness to demand variability. However, it is generally the case that cross‐trained employees are not as productive on a specific task as employees who were originally trained for that task. Also, the productivity of the cross‐trained workers depends on when they are cross‐trained. In this work, we consider a two‐stage model to analyze the effects of variations in productivity levels on cross‐training policies. We define a new metric called achievable capacity and show that it plays a key role in determining the structure of the problem. If cross‐training can be done in a consistent manner, the achievable capacity is not affected when the training is done, which implies that the cross‐training decisions are independent of the opportunity cost of lost demand and are based on a trade‐off between cross‐training costs at different times. When the productivities of workers trained at different times differ, there is a three‐way trade‐off between cross‐training costs at different times and the opportunity cost of lost demand due to lost achievable capacity. We analyze the effects of variability and show that if the productivity levels of workers trained at different times are consistent, the decision maker is inclined to defer the cross‐training decisions as the variability of demand or productivity levels increases. However, when the productivities of workers trained at different times differ, an increase in the variability may make investing more in cross‐training earlier more preferable.     

Redundant configuration of automated flow lines based on “Industry 4.0”-technologies

Over the past decades, robots have been heavily used for flow lines to increase productivity and product quality and to relieve workers of repetitive and dangerous tasks. However, despite continuous improvement of robots, the occurrence of failures remains a significant challenge in the operation of automated flow lines. Due to the connection of the stations in a flow line via a material handling system, failures at one station can quickly lead to throughput losses due to blocking and starving of upstream and downstream stations, respectively. To some extent, these throughput losses can be reduced by installing buffers between the stations. However, the installation of buffers requires considerable investments and scarce factory space. Therefore, the minimization of the total number of buffers is one of the primary objectives in flow line planning. Due to the advances of manufacturing technologies that form the foundation of “Industry 4.0”, new solutions to reduce throughput losses caused by equipment failures open up. One solution is a redundant configuration, in which downstream stations automatically take over the operations of failed stations in the event of failure. The throughput loss in these situations mainly depends on the level of redundancy designed into the system. Based on existing methods for the design of automated flow lines, we present two line balancing formulations for the configuration of automated flow lines under consideration of redundancies. The first formulation aims at maximizing the lines’ level of redundancy. The second formulation aims at a balanced allocation of redundancies along the line. To evaluate the presented formulations, we compare the performance with an existing line balancing approach for automated lines. With respect to this approach, improvements of the throughput rate between 3 % and 7 % are achieved.     

Assembly Line Balancing with Resource Dependent Task Times*

Paced assembly lines are widely used in repetitive manufacturing applications. Most previous research on the design of paced lines has assumed that each task along the line can be performed by only one worker (or a fixed number of workers). In many cases, however, task duration times may be reduced by increasing the number of workers or changing the equipment assigned to work stations. Thus, the problem becomes one of assigning resource alternatives (e.g., workers and/or equipment) and tasks to work stations to minimize total cost for a desired production rate. For this problem, we present three procedures. The first formulates the problem as a shortest path problem and guarantees optimality. The second and third are heuristic adaptations of the shortest path procedure that are capable of solving large problems. The procedures are compared in terms of solution quality and computation time on a set of 128 randomly generated problems for which optimal solutions could be found. Our simulation results indicate that the choice of procedure depends on problem complexity and resource costs.     

Interruption and Forgetting in Knowledge‐Intensive Service Environments

An increasing barrier to productivity in knowledge‐intensive work environments is interruptions. Interruptions stop the current job and can induce forgetting in the worker. The induced forgetting can cause re‐work; to complete the interrupted job, additional effort and time is required to return to the same level of job‐specific knowledge the worker had attained prior to the interruption. This research employs primary observational and process data gathered from a hospital radiology department as inputs into a discrete‐event simulation model to estimate the effect of interruptions, forgetting, and re‐work. To help mitigate the effects of interruption‐induced re‐work, we introduce and test the operational policy of sequestering, where some service resources are protected from interruptions. We find that sequestering can improve the overall productivity and cost performance of the system under certain circumstances. We conclude that research examining knowledge‐intensive operations should explicitly consider interruptions and the forgetting rate of the system's human workers or models will overestimate the system's productivity and underestimate its costs.     

COMPETITIVE MARKETS WITH ENDOGENOUS HEALTH RISKS

We study an economy where agents' productivity and labor endowment depend on their health status, and indivisible occupational choices affect individual health distributions. We show that Pareto efficiency requires cross‐transfers across occupations. Moreover, workers with relatively less safe jobs must get positive transfers whenever labor supply is not very reactive to wages, a condition in line with the findings of a large empirical literature. In these instances, compensating wage differentials equalizing the utilities of ex‐ante identical workers in different jobs undermine ex‐ante efficiency. Moreover, competitive equilibria where only assets with deterministic payoffs are traded are not first‐best. Finally, we show that simple transfer schemes, implemented through linear subsidies to health insurance, enhance efficiency.     

On the Benefits of Risk Pooling in Inventory Management

We analyze the benefits of inventory pooling in a multi‐location newsvendor framework. Using a number of common demand distributions, as well as the distribution‐free approximation, we compare the centralized (pooled) system with the decentralized (non‐pooled) system. We investigate the sensitivity of the absolute and relative reduction in costs to the variability of demand and to the number of locations (facilities) being pooled. We show that for the distributions considered, the absolute benefit of risk pooling increases with variability, and the relative benefit stays fairly constant, as long as the coefficient of variation of demand stays in the low range. However, under high‐variability conditions, both measures decrease to zero as the demand variability is increased. We show, through analytical results and computational experiments, that these effects are due to the different operating regimes exhibited by the system under different levels of variability: as the variability is increased, the system switches from the normal operation to the effective and then complete shutdown regimes; the decrease in the benefits of risk pooling is associated with the two latter stages. The centralization allows the system to remain in the normal operation regime under higher levels of variability compared to the decentralized system.     

Do Foreigners Cushion Native Jobs? The Case of European Regions in the 1990s

Abstract. This paper investigates whether foreigners cushion native labour during the phases of the economic cycle. The theoretical model, based on the work of Blanchard and Katz (Brookings Papers on Economic Activity 0(1): 1–75, 1992), assumes that foreigners supply labour with a higher wage elasticity than natives. The empirical analysis, based on an unbalanced panel of 161 European regions during 1988–97, shows that following a labour demand shock the variability of native employment growth is lower the higher the proportion of foreign citizens in the local labour force. These results suggest that foreigners absorb some of the effects of the shock, shielding natives from its full impact. The analysis also reveals that the main channel mediating this ‘cushioning’ effect is the inter‐regional migration of foreign workers, followed (as a far distant second) by their higher/lower unemployment rates.     

Productivity drift in extended learning curves

The pattern of changes in the Extended Learning Curves representing the performance of 114 assembly workers in an electronics firm is examined in terms of changes in productivity drift over long periods of time. It is shown that 2 types of discontinuities can occur. The first consists of a temporary levelling off in productivity followed by a recovery to new higher levels of productivity; the second has a sustained period of negative productivity drift. A number of work facets are statistically tested as possible causes of these patterns of productivity drift, but, the only significant relationship (at P ≤ 0.05 level) is with length of service in job. Some evidence is presented to show that conventional work measurement methods are not effective in terms of assessing the true work output of experienced workers since such workers are able to beat the system by claiming those allowances which are most difficult to cross-check.     

TEAM INCENTIVES: EVIDENCE FROM A FIRM LEVEL EXPERIMENT

Many organizations rely on teamwork, and yet field evidence on the impacts of team‐based incentives remains scarce. Compared to individual incentives, team incentives can affect productivity by changing both workers’ effort and team composition. We present evidence from a field experiment designed to evaluate the impact of rank incentives and tournaments on the productivity and composition of teams. Strengthening incentives, either through rankings or tournaments, makes workers more likely to form teams with others of similar ability instead of with their friends. Introducing rank incentives however reduces average productivity by 14%, whereas introducing a tournament increases it by 24%. Both effects are heterogeneous: rank incentives only reduce the productivity of teams at the bottom of the productivity distribution, and monetary prize tournaments only increase the productivity of teams at the top. We interpret these results through a theoretical framework that makes precise when the provision of team‐based incentives crowds out the productivity‐enhancing effect of social connections under team production.     

MANAGING A FLOW LINE WITH SINGLE‐KANBAN,DUAL‐KANBAN OR CONWIP

To control the production of different parts on a single flow line, managers can choose between the Single‐kanban, Dual‐kanban, and Conwip. This paper therefore compares the three different systems. The results show that Conwip consistently produces the shortest mean customer wait time and lowest total work‐in‐process. Our results also contradict the finding of a previous study, which showed that Dual‐kanban performed better than Single‐kanban. The different findings can, however, be attributed to the use of a material transfer policy, which favors the Dual‐kanban modeled in the previous study. Our study shows that transferring replenished containers immediately to downstream stations, increasing the number of cards, and reducing the withdrawal cycle reduce the mean customer wait time significantly.     

PERFORMANCE ANALYSIS OF AN ASSEMBLY STATION WITH INPUT FROM MULTIPLE FABRICATION LINES

We develop analytical models for performance evaluation of Fabrication/Assembly (F/A) systems. We consider an F/A system that consists of an assembly station with input from K fabrication lines. Each fabrication line consists of one or more fabrication stations. The system is closed with a fixed number of items circulating between each fabrication line and the assembly station. We present algorithms to estimate the throughput and mean queue lengths of such systems with exponential processing times. We then extend our approach to analyze F/A systems with general processing time distributions. Numerical comparisons with simulations demonstrate the accuracy of our approach.     

The Role of Profit Sharing in Dual Labour Markets with Flexible Outsourcing

We combine profit sharing for high‐skilled workers and outsourcing of low‐skilled tasks in a partly imperfect dual domestic labour market, which means that only low‐skilled labour is represented by a labour union. In that framework we analyse how the implementation of profit sharing for high‐skilled workers influences the amount of outsourcing and the labour market outcome for low‐skilled worker. By doing this, we use some specific assumptions, e.g. exponentially increasing outsourcing costs or the wage for low‐skilled workers will be determined by a union whereas the wage for high‐skilled workers is given. Assuming that low‐skilled labour and outsourcing are interchangeable we show that profit sharing has a positive effect on the wage for low‐skilled workers and helps to decrease wage dispersion. However, under these circumstances, profit sharing enhances outsourcing. Concerning the employment effects for high‐ and low‐skilled workers, we show that there is an employment reducing effect due to higher wages for low‐skilled work, which can be offset by higher productivity of highly skilled workers, as the domestic labour inputs complement each other.     

Schedule Recovery: Unplanned Absences in Service Operations*

The U.S. service sector loses 2.3% of all scheduled labor hours to unplanned absences, but in some industries, the total cost of unplanned absences approaches 20% of payroll expense. The principal reasons for unscheduled absences (personal illness and family issues) are unlikely to abate anytime soon. Despite this, most labor scheduling systems continue to assume perfect attendance. This oversight masks an important but rarely addressed issue in services management: how to recover from short‐notice, short‐term reductions in planned capacity. In this article, we model optimal responses to unplanned employee absences in multi‐server queueing systems that provide discrete, pay‐per‐use services for impatient customers. Our goal is to assess the performance of alternate absence recovery strategies under various staffing and scheduling regimes. We accomplish this by first developing optimal labor schedules for hypothetical service environments with unreliable workers. We then simulate unplanned employee absences, apply an absence recovery model, and compute system profits. Our absence recovery model utilizes recovery strategies such as holdover overtime, call‐ins, and temporary workers. We find that holdover overtime is an effective absence recovery strategy provided sufficient reserve capacity (maximum allowable work hours minus scheduled hours) exists. Otherwise, less precise and more costly absence recovery methods such as call‐ins and temporary help service workers may be needed. We also find that choices for initial staffing and scheduling policies, such as planned overtime and absence anticipation, significantly influence the likelihood of successful absence recovery. To predict the effectiveness of absence recovery policies under alternate staffing/scheduling strategies and operating environments, we propose an index based on initial capacity reserves.     

Optimizing the number of stations in assembly lines under learning for limited production

This paper considers finding the optimal number of stations for an assembly line producing a limited quantity of a new product under learning conditions. This type of production characterizes heavy products (such as airplanes and communication systems) and science-based industries (e.g. laser cutting devices and special equipment for hospitals). These products are manufactured in assembly line fashion in small batches of a few hundred. Since the products are assumed to be totally new to the workers, the learning phenomenon is significant (i.e. task times decrease from cycle to cycle as experience is gained). Therefore, standard balancing methods are no longer applicable. Determining the number of stations has a large effect on the production rate while the actual assignment of tasks to stations helps to fine tune the cycle time. Thus, the number of stations can be regarded as a strategic decision variable . This paper discusses two ways for determining the optimal number of stations, namely as a cost minimization problem and as a profit maximization problem.     

The Role of Firm Size and Performance Pay in Determining Employee Job Satisfaction Brief: Firm Size,Performance Pay,and Job Satisfaction

Abstract. Job satisfaction reflects the on‐the‐job utility of workers and has been found to influence both the behavior of workers and the productivity of firms. Performance pay remains popular and widely used to increase worker productivity and more generally align the objectives of workers and firms. Yet, its impact on job satisfaction is ambiguous. Whereas the increased earnings increase job satisfaction, the increased effort and risk decreases job satisfaction. This paper finds empirical evidence that on net performance pay increases job satisfaction but does so largely among union workers and males in larger firms.     

A Data‐Driven Approach to Assessing Supply Inadequacy Risks Due to Climate‐Induced Shifts in Electricity Demand

The U.S. electric power system is increasingly vulnerable to the adverse impacts of extreme climate events. Supply inadequacy risk can result from climate‐induced shifts in electricity demand and/or damaged physical assets due to hydro‐meteorological hazards and climate change. In this article, we focus on the risks associated with the unanticipated climate‐induced demand shifts and propose a data‐driven approach to identify risk factors that render the electricity sector vulnerable in the face of future climate variability and change. More specifically, we have leveraged advanced supervised learning theory to identify the key predictors of climate‐sensitive demand in the residential, commercial, and industrial sectors. Our analysis indicates that variations in mean dew point temperature is the common major risk factor across all the three sectors. We have also conducted a statistical sensitivity analysis to assess the variability in the projected demand as a function of the key climate risk factor. We then propose the use of scenario‐based heat maps as a tool to communicate the inadequacy risks to stakeholders and decisionmakers. While we use the state of Ohio as a case study, our proposed approach is equally applicable to all other states.     

Knowledge Diversity,Turnover, and Organizational‐Unit Productivity: An Empirical Analysis in a Knowledge‐Intensive Context

We examine the role of knowledge diversity among unit members on an organizational unit's productivity. Utilizing a proprietary data set of corrective maintenance tasks from a large software‐services firm, we investigate the impact of two key within‐unit diversity metrics: interpersonal diversity and intrapersonal diversity. We analyze the independent influence of interpersonal diversity and the interactive influence of interpersonal diversity and intrapersonal diversity on organizational unit's productivity. Finally, we examine how diversity moderates productivity of an organizational unit when employee turnover occurs. Our analysis reveals the following key insights: (a) interpersonal diversity has an inverted U‐shaped effect on organizational unit's productivity; (b) intrapersonal diversity moderates the influence of interpersonal diversity on organizational‐unit productivity; (c) at higher levels of interpersonal diversity, rate of decrease in productivity of the organizational unit due to turnover is higher. We discuss the resulting theoretical and managerial insights associated with these findings.