An exploratory study of disaggregated clearing functions for production systems with multiple products

Clearing functions (CFs) have shown considerable promise for representing production capacity in production planning models due to their ability to capture the non-linear relationships between throughput, order releases and lead times. Most CFs developed to date use the total work in progress of all products, in units of processing time, as the state variable. In this paper, we investigate CFs for multi-product systems where the overall throughput of the system is affected by the product mix. We show that the aggregate work in process (WIP) variable used in the previous CF literature may lead to inaccurate estimates of expected throughput for individual products. To address this issue, we explore the use of multi-dimensional CFs (MDCFs) that use an extended definition of resource state based on the disaggregated WIP levels for individual products. Several new functional forms for MDCFs are postulated for single machine multi-product systems and their ability to represent system behaviour is assessed using simulation experiments. Results reveal that MDCFs are better able to predict system performance in the presence of mix-dependent capacity losses. We also discuss the extension of the MDCF approach to multi-stage production systems.     

Design and storage cycle time analysis for the automated storage system with a conveyor and a rotary rack

In this paper, we analyse the performance of an automated Work-In-Process (WIP) storage system consisting of a conveyor and a rotary rack. The stability condition and the expected storage cycle time are derived to analyse the performance of the WIP storage system. As part of the storage cycle time analysis, the derived expected waiting times at the conveyor and the rotary rack are important performance measures that can be used for buffer-sizing purpose in such systems. Given the fixed storage space of the rotary rack, we also develop a heuristic approach to determine the near optimum ‘shape’ of the rotary rack so that the expected storage cycle time is minimized. Numerical results are presented to examine the storage cycle time model and the proposed shape design. The analytical model introduces a simple approach over simulation with acceptable accuracy; it is useful when designing such WIP storage systems. Moreover, it can be expanded to model more complex systems. The derived model also provides insightful information on the design parameters that a typical simulation tool can hardly provide.     

Performance evaluation and capacity planning in a metallurgical job-shop system using open queueing network models

In this paper, we apply performance evaluation and capacity allocation models to support decisions in the design (or redesign) and planning of a job-shop queueing network of a metallurgical plant. Approximate parametric decomposition methods are used to evaluate system performance measures, such as the expected work-in-process (WIP) and production leadtimes. Based on these methods, optimisation models are then applied for the allocation (or reallocation) of capacity to the stations of the job-shop network. These models are also used to generate approximate trade-off curves between capacity investment and WIP or leadtime, which are valuable for a production manager to estimate how much capacity should be allocated to the stations to reach some targeted performance measures. These curves are also useful for the sensitivity analysis of the solutions to changes in the input parameters, such as the variability of the product demands, the mix of the production and the throughput rate of the network.     

Expected move request waiting times in single-device, polling-based material handling systems

We present an analytical approach to approximate the expected waiting times of move requests (customers) served by a single handling device (server) that operates according to the First-Encountered-First-Served (FEFS) rule, which is a common rule employed for polling-based material handling systems. Under the FEFS rule, the device inspects each station according to a prespecified polling sequence and serves the first move request it encounters. Polling resumes as soon as the device completes serving a move request. The expected waiting times are important for estimating the expected Work-In-Process (WIP) levels at individual stations and to gauge the overall performance of the system. Moreover, the polling sequence itself can affect the expected waiting times. If the device meets the throughput requirement under more than one polling sequence, the results we present can also be used to evaluate alternative polling sequences. In fact, using the analytical results and a numerical example, we show that alternative polling sequences, even if they impose the same “workload factor” on the device, can lead to significantly different expected WIP levels     

Push and pull strategies for controlling multistage production systems

This study considers push and pull strategies to control multistage production systems with random processing times. Such systems are important as they mirror the level of complexity often encountered in practice. We start with definitions of push and pull systems, and develop a framework to compare multistage production systems based upon work-in-process (WIP) and throughput (TP) tradeoff. Surprisingly, we find that often push out performs pull, i.e. push systems accumulate less WIP than pull systems, while maintaining higher PT Concerning pull systems we find that WIP linearly increases in the number of stages and that WIP is not affected by variation in processing time. Concerning push systems we find that the release of material into the system in deterministic time intervals greatly improves performance.     

A dynamic scheduling algorithm for a multiple-load multiple-carrier system

The importance and benefits of using multiple-load carriers in advanced manufacturing systems has been well documented in recent studies. A Dynamic Scheduling Algorithm (DSA) for multiple-load carriers was developed and analysed in the present study using a manufacturing system arranged around a single loop serviced by several multiple-load carriers. In order to evaluate the DSA performance, criteria measures such as throughput, cycle time, WIP and carrier utilization were chosen and compared through simulation with those achieved by three other scheduling rules, Least Work remaining (LWKR), Maximum Utilization (MAX_UT) and First Come First Serve (FCFS). The simulation results also serve to analyse the effect that the carrier fleet size has on the above criteria measures when total carrying capacity is kept constant.     

AMHS capacity determination model for wafer fabrication based on production performance optimization

Automatic material handling system (AMHS) is becoming more important in 300?mm wafer fabrication factories (fab). Effective and efficient design and control of AMHS has become more critical particularly in capacity planning. The major concept of the AMHS capacity determination model is to maintain the originally designed optimal production throughput or cycle time of products. In order to maintain fab’s throughput or cycle time of products, WIP (work in process) portfolio of the constraint or the fastest workstation should be kept. Based on this concept, a GI/G/m queuing model based on FCFS (First-come-first-serve) dispatching rule of AMHS is applied to determine the required number of vehicles. Basically, products should be transported to the specific workstation (constraint or fastest workstation) before the workstation finishes the existing process; therefore, sufficient WIP in front of this specific workstation should be kept. Under this condition, the probability that transportation time exceeds product processing time under a certain transportation capacity level can be calculated by the proposed model. Hence, we can get the required capacity of AMHS to achieve the probability target set in advance. Due to the capacity of AMHS can be set according to the acceptable probability of non-exceeding the processing time of the constraint or fastest workstation, the level of WIP in front of this workstation can be kept. It also can be ensured that AMHS will not affect the production performance as well as keep the reasonable investment level.     

Dynamic card number adjusting strategy in card-based production system

In a production line, throughput rate changes according to WIP (work in process) level and WIP is controlled through the number of production cards in a card-based production system. This paper presents a fast tuning card adjusting procedure using the CONWIP system, which can adjust the number of production cards to ensure desirable throughput rate. The method, termed DTC (difference throughput control), is based on the concept of classic automatic control theory. Whenever a TTH (target throughput value) is set, the difference between TTH and RTH (real time throughput value) is used to adjusting the number of cards. We test this procedure with an existing one in a variety of scenarios; the results show that the proposed procedure is competitive. We also analyse how processing time impacts on the performance of CONWIP system through simulation data.     

An exploratory study of protective inventory in a re-entrant line with protective capacity

While the effect of protective inventory on the performance of simple lines has received considerable attention, the same cannot be said for re-entrant lines. This paper attempts to meet that deficiency. This paper examines two different but related issues. First, the theory of constraints (TOC) evaporating cloud method is employed to show the traditional dilemma of increasing work-in-process (WIP) to fully utilise resources versus decreasing WIP inventory to reduce cycle time. The assumptions and implications of three different management philosophies (traditional, JIT/lean, and TOC) are explored in addressing this dilemma with respect to the use of both protective inventory and protective capacity. Second, given an unbalanced re-entrant line with fixed capacity, simulation is used to explore the effectiveness of using protective inventory by changing the level of WIP on two dependent variables: cycle time and throughput. Two sources of variation are simulated: processing time and breakdowns (machine failures). At a given WIP level, it was found that the amount of protective capacity at non-bottlenecks changed with increases in variability. Therefore the level of WIP inventory (with its protective inventory) and the level of protective capacity needed to protect against variability play a critical role in determining cycle time and throughput of the re-entrant line. While this is an exploratory study, comments on protective inventory and protective capacity are provided based on the three different management philosophies.     

Total WIP and WIP mix for a CONWIP controlled job shop

A planning procedure to set the constant level of Work-In-Process (WIP) for each product type in a job shop operated under CONWIP control is developed. We model the job shop as a single chain multiple class closed queuing network. Given a specified product mix and a total WIP, a nonlinear program bounds the throughput of the network and optimizes the WIP mix. We identify the minimum total WIP that is guaranteed to yield throughput near the maximum possible for the specified product mix and set individual WIP levels by multiplying the optimal WIP mix proportions by the minimum total WIP. Numerical examples illustrate how these individual product WIP levels achieve the goal of high throughput consistent with the specified product mix.     

Job order releasing and throughput planning for multi-priority orders in wafer fabs

To meet the production target of multi-level (multiple priority rank) orders in wafer fabs, this paper uses a hierarchical framework based on a mathematical model, and without the assistance of any simulation tool, to build a production scheduling system to plan wafer lot releasing sequence and time. This system first applies capacity loading analysis to set up the batch policy for each level (rank) of orders. Next, the production cycle time of each product level is estimated with considerations of batching and loading factor. The cycle time is then used to derive system control parameters such as the most appropriate level of work in process (WIP) and the number of daily operations on the bottleneck workstation. Lastly, a Constant WIP mechanism is applied to establish a wafer release sequence table and a throughput timetable. The due date designation for each specific order can hence be confirmed. With the comparison with the result of simulation, it shows that under the designed system the performance and planning measures in the master production schedule can be drawn up quickly and accurately, and the system throughput target and due date satisfaction can be achieved. Overall, the proposed production scheduling system is both effective and practicable, and the planning results are supportive for good target planning and production activity control.     

Optimal batching in a wafer fabrication facility using a multiproduct G/G/c model with batch processing

Wafer fabrication, the first portion of semiconductor manufacturing, typically involves numerous batch-processing operations. These operations play an important role in determining how the system performs in terms of throughput, WIP and cycle time. In this paper, batch sizes that minimize the expected cycle time of batch-processing operations for a real-world semiconductor manufacturer are determined by a new approximated analytical model. This model, denoted by G / G ( bp ) , represents multiple products, multiple servers, batch-processing, incompatible products and unequal batch service size queues. Incompatible products mean that different products are not allowed to be in the same batch. Unequal batch service size means that batch service sizes depend upon products. Steady-state approximation formulas for cycle time and WIP of this queuing system are derived. These approximate performance measures are compared with those of discrete-event simulation. The results are reasonable and the approximation formulas much more computationally efficient than conducting the corresponding simulation studies. Finally, a batch-processing system with the goal of minimizing the total expected cycle times of items by determining the 'optimal' batch sizes is presented. Solutions are obtained using genetic algorithms.     

Optimal stack layout in a sea container terminal with automated lifting vehicles

Container terminal performance is largely determined by its design decisions, which include the number and type of quay cranes, stack cranes, transport vehicles, vehicle travel path and stack layout. We investigate the orientation of the stack layout (parallel or perpendicular to the quayside) on the throughput time performance of the terminals. Previous studies in this area typically use deterministic optimisation, and a few studies use probabilistic travel times and simulation to analyse the effect of stack layout on terminal throughput times. In this research, we capture the stochasticity with an integrated queuing network modelling approach to analyse the performance of container terminals with parallel stack layout using automated lifting vehicles. Using this analytical model, we investigate 1008 parallel stack layout configurations on throughput times and determine the optimal stack layout configuration. We find that, assuming an identical width of the internal transport area, container terminals with parallel stack layout perform better (from 4–12% in terms of container throughput times) than terminals with a perpendicular stack layout.     

Determining inventory levels in a CONWIP controlled job shop

We extend the concept of CONWIP control to a job shop setting, in which multiple products with distinct routings compete for the same set of resources. The problem is to determine the fixed overall WIP level and its allocation to product types (WIP mix) to meet a uniformly high customer service requirement for each product type. We formulate an optimization problem for an open queuing network model in which customer orders pull completed products from the system. Then, assuming heavy demand, we derive a throughput target for each product type in a closed queuing network and provide a simple heuristic to find a minimum total WJP and WIP mix that will achieve an operating throughput close to this target. In numerical examples, the WIP mix suggested by this approach achieves the customer service requirement with a relatively low total WIP     

Critical WIP loops: a mechanism for material flow control in flow lines

Critical WIP loops (CWIPL) is a proposed material flow control mechanism for a balanced flow line environment aiming at improving throughput and lead time. The mechanism establishes critical loops which their WIP identifies the time of releasing raw material to the line. So, through control of WIP level of critical loops the material flow is managed. The proposed mechanism releases the raw material to the line if the ‘total WIP of the line’ or ‘the WIP of the last machine’ is less than the limit. Besides the aforementioned condition, the necessary condition for releasing the raw material to the line is ‘idleness of the first machine’. Simulation is used to compare the performance of the CWIPL, CONWIP and G-MaxWIP. Different line characteristics such as number of machines, processing time distributions and the maximum WIP level of the line are considered in numerical examples. The results show that CWIPL improves both throughput and lead time compared with CONWIP, while CWIPL has better results than G-MaxWIP with respect to both throughput and lead time in the flow line that has less than nine machines.     

Gated MaxWIP: A strategy for controlling multistage production systems

This study considers serial production systems with exponential processing times. The systems are balanced, i.e. all resources have the same production rate capacity. Preceding the system there is a 'gate' set to regulate the flow of material into the system. A control strategy directs each resource when to work or stay idle. The trade-off is between throughput (TP) and work-in-process (WIP). G-MaxWIP is a production control strategy allowing resources, except for the gate, to work unconstrained. The gate 'shuts' once the system's WIP reaches a maximum allowable level. We study the properties of G-MaxWIP and compare it to 'simple pull' and CONWIP. Our main findings are: G-MaxWIP is superior to simple pull. For any simple pull system operating a fixed set of resources it is possible to find G-MaxWIP systems that operate the same resources with less WIP while maintaining the same (or higher) TP. G-MaxWIP is superior to CONWIP. For any CONWIP system operating a fixed set of resources it is possible to find G-MaxWIP systems that operate the same resources with less WIP while maintaining the same (or higher) TP.     

OSL—optimal single-loop guide paths for AGVS

This study deals with the Automated Guided Vehicle System guide path design problem. We suggest a single closed loop guide path layout configuration as an alternative to conventional but more complex guide path designs. The benefits of using a simple guide path versus more complicated guide paths are discussed. A procedure for designing an optimal single loop guide path for a given facility layout is presented. Finally, the single loop's throughput performance is tested and compared to that of a more complex guide path.     

A simulation study of CONWIP assembly with multi-loop in mass production,multi-products and low volume and OKP environments

This paper studies the performance of constant work-in-process (CONWIP) assembly system with multi-loop in mass production, multi-products and low volume and one-of-a-kind production (OKP) environments using simulation. We propose five basic design patterns of CONWIP loop and develop eight control policies of CONWIP loop based on the design pattern for standard assembly system. The performance of developed loop policies is evaluated in three production environments. In particular, control policies of CONWIP loop in OKP environment provide a valuable reference for OKP shop floor controlling. A heuristic algorithm of searching work-in-process (WIP) upper bound, the deadlock phenomenon in CONWIP assembly system and suggestion are introduced specifically. The summary of CONWIP installation guidelines in the mixed assembly system can apply CONWIP theory to practise.     

Solving coupled task assignment and capacity planning problems for a job shop by using a concurrent genetic algorithm

The problems of task assignment and capacity planning of manufacturing systems have been researched for many years. However, in the existing literature, these two types of problems are researched independently. Namely, when solving the task assignment problem, it is usually assumed that the production capacity of the manufacturing systems has been determined. On the other hand, when solving the capacity planning problem, the production tasks assigned to the workstations in the manufacturing system have also been determined. Actually, the task assignment problem and the capacity planning problem are coupled with each other. When we assign production tasks to workstations, production capacities of these workstations should be regulated so that they are enough for completing the tasks. At the same time, when planning the production capacity, we must know what production tasks are assigned to what workstations. This research focuses on the coupling relations between the two problems for a closed job shop, in which the total work-in-process (WIP) is assumed to be constant. The objective of the task assignment problem is to balance the workloads of the workstations and the objectives of the capacity planning problem are maximising the throughput and minimising total costs of machine purchasing and WIP inventory. We construct the fundamental system architecture for controlling the two coupled optimisation processes, and propose a concurrent genetic algorithm (CGA) to solve the two coupled optimisation problems. The influences of the decision variables of one problem on the objective function of the other problem are taken into consideration when the fitness functions of the CGA are constructed. Numerical experiments are done to verify the effectiveness of the algorithm.     

Performance of carousel systems with ‘organ-pipe’ storage

It is well known that, for carousel systems, a dedicated storage, referred to as the ‘organ-pipe’ storage in the literature, is optimal with respect to the expected travel distance for processing successive requests. What remains unanswered is how to determine its performance, which is the motivation of this study. We consider bi-directional carousels under a ‘floating’ dwell point strategy. Two important performance measures considered are system capacity (maximum throughput) and job sojourn time. We also investigate the effect of activity skew on system performance.