Decentralized WIP-oriented manufacturing control (DEWIP)

DEWIP is a manufacturing control system for job shop environments aiming at achieving short and reliable lead times by establishing WIP control loops between the manufacturing work centres. The paper describes the mode of function, the setting of parameters and simulation results of the new manufacturing control system. The setting of parameters is done with the aid of the funnel model and the theory of logistic operating curves, both developed at the Institute of Production Systems at the University of Hanover. The simulation is conducted using industrial data and makes it possible to assess DEWIP with regard to lead times, WIP level, performance and schedule reliability. DEWIP is compared both with an uncontrolled process and with the manufacturing control systems Load oriented order release (LOOR), Conwip and Polca. The results suggest that DEWIP and the models employed for the setting of parameters are suitable for job shop production and therefore offer a valuable alternative to prevailing centralized manufacturing control systems.     

A New Framework for Manufacturing Planning and Control Systems*

This paper presents a new framework for manufacturing planning and control systems which we call iterative manufacturing planning in continuous time (IMPICT) that appears to have several advantages over the well-known material requirements planning (MRP) framework. IMPICT explicitly considers capacity constraints and total system cost (including tardiness) to determine order sizes, order release/due dates, and operation schedules in a deterministic, multi-level, finite horizon, dynamic demand environment. Continuous time scheduling variables allow setups to be carried over from one period to the next. Three new heuristics built on the IMPICT framework are presented and tested in a simulation-based, full-factorial experiment with a wide variety of problem environments. The benchmark for the experiment was materials requirements planning with operations sequencing (MRP/OS) implemented with best-case, fixed planned lead times. The experiment showed that all three heuristics were statistically better than MRP/OS. The total cost for the order merging (OM) heuristic was 25 percent better than the total cost for MRP/OS. Computational times for OM were substantially larger than for MRP/OS; however, the computational times in the experiment suggest that OM is still computationally viable for large-scale batch manufacturing environments found in industry. IMPICT is superior to standard MRP systems because it explicitly considers capacity constraints and total system costs when it creates a materials plan. IMPICT is superior to linear programming-based approaches to finite loading and scheduling found in the literature because it allows setups to be carried over from one period to another and because it is computationally viable for realistic-sized problems.     

An investigation of output flow control,bottleneck flow control and dynamic flow control mechanisms in various simple lines scenarios

Flow control mechanisms have been a topic of academic research for several years. With the growth of business-wide information systems such as enterprise resource planning and supply chain, better planning, scheduling and control of the business transformation process is required in order to achieve increased throughput, reduced inventories, shorter lead times and reduced tardiness. This research compares two new approaches to flow control, output flow control and bottleneck flow control to a real-time flow control system, dynamic flow control. Both output and bottleneck flow control mechanisms are much simpler to implement and manage than dynamic flow control in that they do not require continual feedback and rescheduling. Line characteristics, such as location of breakdowns with respect to the bottleneck, the location of the bottleneck when breakdowns occur, and the impact of variability of processing times on the performance measures (output, WIP level, lateness, and number of tardy jobs) for these three flow control mechanisms are compared. Both output and bottleneck flow control mechanisms perform favourably (particularly bottleneck) under different scenarios and warrant further study across a wider range of scenarios (mixed models, job shops, etc.).     

Lead time adjustment through scrap management

In a discrete parts manufacturing environment, it is necessary to compensate for the decreasing planned batch size resulting from production of scrap (defectives) in the production line, by increasing the planned production volume. This calls for a revision in the initially computed manufacturing lead time (MLT). A survey of the literature reveals that although issues related to product quantity regeneration have been studied in detail, little has been done to assess the impact on manufacturing lead times. This paper discusses the impact of scrap on manufacturing lead time in a shop with an intermittent-flow, bath-oriented, discrete-parts manufacturing environment, producing make-to-stock items.     

一类新型批处理机调度问题的理论分析

钢卷在冷轧生产中,为了改进其性能,需要在罩式炉进行退火,退火过程由加热、保温和降温三段组成,而这三段处理时间由于工艺上的要求不能归结为一个时间,这与传统批处理机调度有明显的差别.对新型批处理机的总加权完成时间最小化问题建立了非线性整数规划模型,开发了基于动态规划的启发式算法.通过理论分析,获得该算法的误差性能比为3.对于三段中的某一段板卷的处理时间相同的情况,证明了启发式算法的误差性能比是2,而且证明是紧界.对于三段中的某二段板卷的处理时间相同的情况,证明了启发式算法是最优算法.对启发式算法扩展到带有任意段的加工时间的一般情况进行了性能分析.     

Hierarchical Multi‐skill Resource Assignment in the Telecommunications Industry

We formulate a discrete time Markov decision process for a resource assignment problem for multi‐skilled resources with a hierarchical skill structure to minimize the average penalty and waiting costs for jobs with different waiting costs and uncertain service times. In contrast to most queueing models, our application leads to service times that are known before the job is actually served but only after it is accepted and assigned to a server. We formulate the corresponding Markov decision process, which is intractable for problems of realistic size due to the curse of dimensionality. Using an affine approximation of the bias function, we develop a simple linear program that yields a lower bound for the minimum average costs. We suggest how the solution of the linear program can be used in a simple heuristic and illustrate its performance in numerical examples and a case study.     

Assessment of Patient Classification in Appointment System Design

This paper investigates two approaches to patient classification: using patient classification only for sequencing patient appointments at the time of booking and using patient classification for both sequencing and appointment interval adjustment. In the latter approach, appointment intervals are adjusted to match the consultation time characteristics of different patient classes. Our simulation results indicate that new appointment systems that utilize interval adjustment for patient class are successful in improving doctors' idle time, doctors' overtime and patients' waiting times without any trade‐offs. Best performing appointment systems are identified for different clinic environments characterized by walk‐ins, no‐shows, the percentage of new patients, and the ratio of the mean consultation time of new patients to the mean consultation time of return patients. As a result, practical guidelines are developed for managers who are responsible for designing appointment systems.     

Some heuristic algorithms for total tardiness minimization in a flowshop with blocking

The flowshop scheduling problem with blocking in-process is addressed in this paper. In this environment, there are no buffers between successive machines; therefore intermediate queues of jobs waiting in the system for their next operations are not allowed. Heuristic approaches are proposed to minimize the total tardiness criterion. A constructive heuristic that explores specific characteristics of the problem is presented. Moreover, a GRASP-based heuristic is proposed and coupled with a path relinking strategy to search for better outcomes. Computational tests are presented and the comparisons made with an adaptation of the NEH algorithm and with a branch-and-bound algorithm indicate that the new approaches are promising.     

考虑分时电价的多目标批调度问题蚁群算法求解

对同时优化电力成本和制造跨度的多目标批处理机调度问题进行了研究,设计了两种多目标蚁群算法,基于工件序的多目标蚁群算法(J-PACO,Job-based Pareto Ant Colony Optimization)和基于成批的多目标蚁群算法(B-PACO,Batch-based Pareto Ant Colony Optimization)对问题进行求解分析。由于分时电价中电价是时间的函数,因而在传统批调度进行批排序的基础上,需要进一步确定批加工时间点以测定电力成本。提出的两种蚁群算法分别将工件和批与时间线相结合进行调度对此类问题进行求解。通过仿真实验将两种算法对问题的求解进行了比较,仿真实验表明B-PACO算法通过结合FFLPT(First Fit Longest Processing Time)启发式算法先将工件成批再生成最终方案,提高了算法搜索效率,并且在衡量算法搜索非支配解数量的Q指标和衡量非支配集与Pareto边界接近程度的HV指标上,均优于J-PACO算法。     

The Ordered Cutting Stock Problem

The one‐dimensional cutting stock problem (CSP) is a classic combinatorial optimization problem in which a number of parts of various lengths must be cut from an inventory of standard‐size material. The classic CSP ensures that the total demand for a given part size is met but ignores the fact that parts produced by a given cutting pattern may be destined for different jobs. As a result, applying the classic CSP in a dynamic production environment may result in many jobs being open (or partially complete) at any point in time—requiring significant material handling or sorting operations. This paper identifies and discusses a new type of one‐dimensional CSP, called the ordered CSP, which explicitly restricts to one the number of jobs in a production process that can be open, or in process, at any given point in time. Given the growing emphasis on mass customization in the manufacturing industry, this restriction can help lead to a reduction in both in‐process inventory levels and material handling activities. A formal mathematical formulation is provided for the new CSP model, and its applicability is discussed with respect to a production problem in the custom door and window manufacturing industry. A genetic algorithm (GA) solution approach is then presented, which incorporates a customized heuristic for reducing scrap levels. Several different production scenarios are considered, and computational results are provided that illustrate the ability of the GA‐based approach to significantly decrease the amount of scrap generated in the production process.     

Concerning Workload Control and Order Release: The Pre‐Shop Pool Sequencing Decision

Every production planning concept that incorporates controlled order release will initially withhold jobs from the shop floor and create a pre‐shop pool. Order release is a key component of the Workload Control concept that aims to maintain work‐in‐process within limits while ensuring due dates are met. Order release includes two decisions: (i) a sequencing decision that establishes the order in which jobs are considered for release; and, (ii) a selection decision that determines the criteria for choosing jobs for release. While selection has received much research attention, sequencing has been largely neglected. Using simulation, this study uncovers the potential for performance improvement in the sequencing decision and improves our understanding of how order release methods should be designed. Although most prior studies apply time‐oriented sequencing rules and load‐oriented selection rules, analysis reveals that load balancing considerations should also be incorporated in the sequencing decision. But an exclusive focus on load balancing is shown to increase mean tardiness and, paradoxically, require high workloads. A new sequencing rule is developed that only balances loads when multiple orders become urgent. It avoids high mean tardiness and allows the shop to operate at a low workload level. At the same time, the percentage tardy is reduced by up to 50% compared to a purely time‐oriented rule. The findings have implications not only for Workload Control but for any concept that features order release control, such as ConWIP and Drum‐Buffer‐Rope.     

An investigation of order release and flow time allowance policies for assembly job shops

The effects of a number of essentially different work order release and flow time allowance policies on the assembly order flow times and assembly order due date performance are investigated. Work orders within an assembly order have different routing length. The assembly order flow time is the time that elapses between the release of the first work order and the completion of the last work order of the assembly order. The timing of the release of work orders, and the distribution of the flow time allowance over the work orders in an assembly order were varied, and used systematic computer simulation to investigate the effects on performance. The results show that the best performance is obtained with simultaneous work order release, an average operation flow time allowance equal to the average operation waiting time and equalized flow time allowances per work order in an assembly order.     

Modeling and Managing the Percentage of Satisfied Customers in Hidden and Revealed Waiting Line Systems

We perform an analysis of various queueing systems with an emphasis on estimating a single performance metric. This metric is defined to be the percentage of customers whose actual waiting time was less than their individual waiting time threshold. We label this metric the Percentage of Satisfied Customers (PSC.) This threshold is a reflection of the customers' expectation of a reasonable waiting time in the system given its current state. Cases in which no system state information is available to the customer are referred to as “hidden queues.” For such systems, the waiting time threshold is independent of the length of the waiting line, and it is randomly drawn from a distribution of threshold values for the customer population. The literature generally assumes that such thresholds are exponentially distributed. For these cases, we derive closed form expressions for our performance metric for a variety of possible service time distributions. We also relax this assumption for cases where service times are exponential and derive closed form results for a large class of threshold distributions. We analyze such queues for both single and multi‐server systems. We refer to cases in which customers may observe the length of the line as “revealed” queues.“ We perform a parallel analysis for both single and multi‐server revealed queues. The chief distinction is that for these cases, customers may develop threshold values that are dependent upon the number of customers in the system upon their arrival. The new perspective this paper brings to the modeling of the performance of waiting line systems allows us to rethink and suggest ways to enhance the effectiveness of various managerial options for improving the service quality and customer satisfaction of waiting line systems. We conclude with many useful insights on ways to improve customer satisfaction in waiting line situations that follow directly from our analysis.     

RFID as an Enabler of Improved Manufacturing Performance*

The use of radio frequency identification (RFID) versus bar coding has been debated with little quantitative research about how to best use RFID's capabilities and when RFID is more advantageous. This article responds to that need by qualitatively and quantitatively analyzing how RFID facilitates increased traceability and control in manufacturing, which in turn enables the use of more lot splitting and smaller lot sizes. We develop insights about operating policies (RFID vs. bar‐code tracking mechanisms, extent of lot splitting, and dispatching rules) and an operating condition (setup to processing time ratio) that affect the mean flow time and proportion of jobs tardy in a job shop. A simulation model is used to control factors in the experimental design and the output is evaluated using analysis of variance. The results show the following: (i) performance worsens when bar coding is used with extensive lot splitting, (ii) process changes such as extensive lot splitting may be required to justify RFID use instead of bar coding, (iii) the earliest operation due date dispatching rule offers an attractive alternative to other rules studied in previous lot splitting research, and (iv) the performance improvements with RFID and increased lot splitting are larger when the setup to processing time ratio is smaller. In a broader context, we fill a research void by quantitatively showing how RFID can be used as an advanced manufacturing technology that enables more factory automation and better performance along several dimensions. The article concludes by summarizing the results and identifying ideas for future research.     

Vendor Performance and Alternative Manufacturing Environments*

Today, many American firms are demanding a high level of performance from their major suppliers while at the same time reducing the number of them. Vendor performance is an important aspect of maintaining low production costs and high product quality. In this study, we examine the effects of poor vendor quality and vendor lead time uncertainty in a variety of manufacturing environments using a comprehensive simulation model. The results indicate that the effect of poor vendor performance on various manufacturing firms depends on the number of stocking points and the degree of component commonality. Moreover, disruption of the manufacturing system caused by poor vendor performance can be manifested in higher levels of inventory and order backlogs. We introduce the concept of supplyside uncertainty, as it relates to component-part commonality, to demonstrate that in certain environments commonality reduces order backlogs but increases total inventories and creates an environment that is very sensitive to vendor quality problems. Finally, several conjectures are posited for future research.     

A heuristic approach to n/ m job shop scheduling: fuzzy dynamic scheduling algorithms

n/m shop scheduling is a ‘ NP-Hard’ problem. Using conventional heuristic algorithms ( priority rules) only, it is almost impossible to achieve an optimal solution. Research has been carried out to improve the heuristic algorithms to give a near-optimal solution. This paper advocates a fuzzy logic based, dynamic scheduling algoridim aimed at achieving this goal. The concept of new membership functions is discussed in die algorithm as a link to connect several priority rules. The constraints to determine the membership function of jobs for a particular priority rule are established, and three membership functions are developed. In order to decide the weight vector of priority rules, an aggregate performance measure is suggested. The methodology for constructing the weight vector is discussed in detail. Experiments have been carried out using a simulation technique to validate the proposed scheduling algorithm.     

Job Shop Scheduling With Deadlines

In this paper we deal with a variant of the Job ShopScheduling Problem. We consider the addition of release dates anddeadlines to be met by all jobs. The objective is makespanminimization if there are no tardy jobs, and tardiness minimizationotherwise. The problem is approached by using a Shifting Bottleneckstrategy. The presence of deadlines motivates an iterative use of aparticular one machine problem which is solved optimally. Theoverall procedure is heuristic and exhibits a good trade-off betweencomputing time and solution quality.     

Lean Control for Make‐to‐Order Companies: Integrating Customer Enquiry Management and Order Release

A lead time that is short, predictable, and reliable is an increasingly important criterion in supplier selection. Although many companies may achieve this through lean implementation, high‐variety manufacturers, for example, small and medium‐sized make‐to‐order companies, have found that lean's planning and control techniques do not apply. This article outlines a planning and control concept known as workload control (WLC) that integrates customer enquiry management, including a due‐date setting rule, with order release control. Simulation is then used to assess its impact on shop performance. Results demonstrate that an integrated WLC concept can reduce the percentage of tardy jobs—so short lead times can be realistically quoted—while also reducing and stabilizing workloads. WLC can level demand and production over time when work is not standardized and it is not possible to synchronize flows on the shop floor. Results are shown to be robust to changes in routing characteristics, the mix of orders with due dates specified by the customer and proposed internally, and the strike rate (or order‐winning probability). Hence, an integrated approach to WLC represents an important step toward achieving lean in make‐to‐order companies.     

The effect of MRP lot sizing on actual cumulative lead times in multi-level systems

This study investigates how different lot sizing techniques influence the cumulative lead time for multi-level production-inventory systems controlled by material requirements planning (MRP). Theoretical approaches, a numerical example, as well as simulation are used to analyse and illustrate the combined effect of lot sizing at different product structure levels. It is shown that lot-sizing requirements for more than a single period, such as fixed period requirements, period under quantity, Silver Meal algorithm, as well as economic order quantity will lead to longer actual cumulative lead times than would be expected, when taking the item lead times along the critical path through the product structure into account. Consequently, MRP will underestimate the cumulative lead time and will require a longer planning horizon. We show that the extension of the cumulative lead techniques covering the time is a lot-sizing related phenomenon and cannot be accounted for by, e.g. using safety lead time. Lot-sizing techniques with multi-period coverage will only occasionally provide the 'expected' cumulative lead time. We also show that average and maximum throughput times, as well as throughput time variability increases with increasing time-period coverage of lots.