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.     

Inspection allocation for multistage deteriorating production systems

The paper deals with the layout and operation of an inspection system used for detecting malfunctioning processors in a multistage production system. This problem involves three inter-related decisions: (i) the overall inspection capacity; (ii) the assignment of inspection tasks to inspectors; and (iii) the scheduling of the inspector's tasks. These decisions require a trade-off between the cost of inspectors and the loss associated with non-conforming products. A hierarchical heuristic solution procedure is proposed to support these three related decisions. Numerical experiments demonstrate the performance of the heuristic, showing that solution criteria are very close to their lower bounds. Although we use production terminology, the results might be applicable to any organization, which inspects and maintains a variety of characteristics of its branches or activities.     

Inspection allocation for multistage deteriorating production systems

The paper deals with the layout and operation of an inspection system used for detecting malfunctioning processors in a multistage production system. This problem involves three inter-related decisions: (i) the overall inspection capacity; (ii) the assignment of inspection tasks to inspectors; and (iii) the scheduling of the inspector's tasks. These decisions require a trade-off between the cost of inspectors and the loss associated with non-conforming products. A hierarchical heuristic solution procedure is proposed to support these three related decisions. Numerical experiments demonstrate the performance of the heuristic, showing that solution criteria are very close to their lower bounds. Although we use production terminology, the results might be applicable to any organization, which inspects and maintains a variety of characteristics of its branches or activities.     

Optimal and heuristic inspection schedules for multistage production systems

Consider a single inspection facility that can be quickly switched among multiple inspection tasks. It can be used (for example) for detecting malfunction (or down state) production stages in a multistage production system. We assume that a properly working (or up state) production stage moves to a down state in any period with fixed probability. The stage then stays down until it is inspected and immediately restored back to an up state. Our purpose is to schedule inspections among the different production stages so as to maximize the fraction of good items produced. An optimal inspection schedule for a two stage production system is provided. For the general case of more than two stages, four heuristics are compared. We conclude that the proposed dynamic schedule is easy to derive, always feasible, and outperforms the static schedules.     

Inspection strategies for multistage production systems with time-varying quality

An economic, cost of quality model is formulated for a production system with multiple inspection locations and sampling. The model is applied to a thermal printer for digital photographs to determine when inspection of incoming material is appropriate. A simple dynamic model of quality is used, allowing for common-cause defects and the evaluation of sampling plans. The opportunity to correct quality problems more quickly when they are detected earlier is also considered. The cost structure used allows the costs of quality improvement, and not just that of defective units, to be considered.     

A study of the optimal production strategy for hybrid production systems

Due to increased environmental awareness, the issue of recycling and disassembling damaged or malfunctioning products after consumption to obtain useable parts for remanufacturing has become essential. This study considers a hybrid production system with both external and internal reverse logistics in which the external recycled products are utilised for remanufacturing to satisfy demand first, and then the ordinary manufacturing process may supplement this if there is any shortage in production. In addition, the defective items produced internally by either the manufacturing or the remanufacturing process can also be repaired by a remediation process. The objective of this study is to determine the optimal strategy for the manufacturing, remanufacturing, disposal, and remediation rates. Three conditions are considered in which the production strategy varies with different yield rates and capacity limits. The impacts of related factors on the production strategy are investigated to probe the trade-offs between product consumption and environmental protection.     

Optimization of multistage production systems with variable production times and costs

Introducing a concept of ‘ production speed ’ as a decision variable, a production model with variable (speed-dependent) production time and cost for producing a product item was constructed. Optimization analysis was mode on a single-item, multistage production system in an attempt to determine the optimal production speeds for all stages and the optimal cycle time. For a case of multiple-item production, an optimal job sequence and the optimal production speeds for all jobs were analysed, such that the total flow time was minimized as a primary objective and, in addition, the total production cost was minimized as a secondary objective.     

Computation reduction for a large-scale Markov process model to analyse multistage production systems

In order to solve a large-scale Markov decision process which optimizes the control strategy of a multistaged production/inventory system, a computation reduction and memory management system was used. A ‘nuclear’ state space of relatively small size was found to substitute for the original state space. A circular comparison technique and a location index storage method were used to save computer memory used for storing the model     

An event-based analysis of condition-based maintenance decision-making in multistage production systems

Condition-based maintenance (CBM) is becoming increasingly prevalent because of its capability to continuously track equipment health degradation and accurately predict unscheduled equipment failure. CBM helps to improve the business bottom line by preventing costly station failure. However, it is not uncommon that CBM needs to stop stations for maintenance during operation, which can severely impede the normal production. The objective of this paper is to develop a systematic method to predict the negative impact of CBM stoppage events on production in a multistage manufacturing system. The research helps to predict the real expense of applying CBM, which is the foundation to establish a comprehensive real-time CBM decision-making model. We start from the event-based analysis of system dynamics and develop a stochastic estimation method to predict the permanent production loss caused by a CBM stoppage event. The monotonicity property of permanent production loss is investigated. Simulation case studies are performed to illustrate the theoretical results and demonstrate their potential in facilitating CBM decision-making.     

A self-starting procedure for monitoring process quality in multistage manufacturing systems

Manufacturing systems typically contain processing and assembly stages whose output quality is significantly affected by the output quality of preceding stages. The deficiencies of using standard statistical process-monitoring procedures in such systems have been highlighted in the literature. This article proposes a procedure to monitor process and product quality in multistage systems. By accounting for the quality of the input to each stage, the procedure not only detects the presence of out-of-control conditions but also helps to identify the stages responsible for such departures. We extend previous research to the common case where the process parameters are unknown. An extensive performance study shows that the procedure is effective in detecting out-of-control conditions and that it convincingly outperforms existing methods. We illustrate the use of the procedure using production line data from a major electronics manufacturer.     

Optimal production planning for a multiproduct,multistage production system

A mathematical model of production planning for a multiproduct, multistage produetionaystom (production equation, transition equation and objective function) was constructed in order to derive the optimal decision rule to be adapted to demand fluctuation. With this model the optimal solution and the computational algorithm were determined by functional space approach. With use of this algorithm, a numerical example of optimal production planning was solved.     

A strategy for identification of oligosaccharide structures using observational multistage mass spectral library

Glycosylation is the most widespread posttranslational modification in eukaryotes; however, the role of oligosaccharides attached to proteins has been little studied because of the lack of a sensitive and easy analytical method for oligosaccharide structures. Recently, tandem mass spectrometric techniques have been revealing that oligosaccharides might have characteristic signal intensity profiles. We describe here a strategy for the rapid and accurate identification of the oligosaccharide structures on glycoproteins using only mass spectrometry. It is based on a comparison of the signal intensity profiles of multistage tandem mass (MSn) spectra between the analyte and a library of observational mass spectra acquired from structurally defined oligosaccharides prepared using glycosyltransferases. To smartly identify the oligosaccharides released from biological materials, a computer suggests which ion among the fragment ions in the MS/MS spectrum should yield the most informative MS3 spectrum to distinguish similar oligosaccharides. Using this strategy, we were able to identify the structure of N-linked oligosaccharides in immunoglobulin G as an example.     

Stage due date planning for multistage assembly systems

Coordinating due dates of operations throughout all stages of manufacturing and assembly is a problem especially for complex product structures with uncertainties in process times. A recursive procedure is described to estimate distributions of completion times for each operation. Stage due dates are then calculated to meet specified service targets. Compared with plans from existing heuristic methods, there are considerable improvements in meeting service targets and reducing costs. Simulations demonstrate that the method is effective for complex assemblies produced in low volumes by capital goods companies.     

A pattern-recognition-based method for controlling a multi-loop production system

The control of an equipment-intensive production system in the electronics industry is a very complicated task due to the complex process flow, especially the necessity for several loop sequences of the same processes.

This paper describes the development of a pattern-recognition-oriented control-decision support system (CDSS) in order to set the best control strategy and an application for a circuit board fabrication system. The CDSS has been designed to be flexible to adapt to a change of market demands. This procedure is based on the state table concept.

A combined discrete-event/process-interaction simulation model for the production system has been developed in order to provide basic data for the CDSS. The simulation analysis evaluates the alternatives of the control strategy on the efficiency performances, such as throughput and WIP.     

Mode-specific strategy for controlling a single-molecule reaction

Inelastic tunnelling electrons are a proper excitation source to induce chemical transformations on a single adsorbate. When their energy is tuned to that of molecular vibrational states, the modification may follow complex internal vibrational pathways. Here, we analyse our recent results on the selective excitation of ammonium stretching or bending modes to control the outcome of a simple bond-cleavage reaction. With the help of model calculations, we provide a detailed molecular-scale picture of the competing internal pathways leading to molecular movement. A mode-selective strategy, based on local excitations of specific reaction coordinates, has an important drawback when applied to adsorbate systems due to the problem of fast energy randomization. The success of such a mode-selective strategy is determined here by the ability of the scanning tunnelling microscope to study reactivity in the limit of very low yield and very low power irradiation, in a regime where vibrational heating of the adsorbate/surface system becomes negligible.     

A coordination strategy for distributed multi-agent manufacturing systems

This paper proposes a distributed multi-agent approach for dynamic part routing in automated manufacturing systems. In particular, each part in the system is associated to an intelligent software agent that must select its next destination autonomously (i.e. ignoring the actions of the other agents) and in real time (i.e. at each time it completes an operation on a workstation). Differently from other existing approaches, we overcome the typical myopia of negotiation algorithms based on dispatching rules by allowing the part agents to take decisions not only about the imminent operation, but also for the subsequent ones. The anticipated decisions are transmitted to workstation agents, which are also designated to detect and resolve conflicts by modifying part agents’ decisions. To describe the single agents and their interaction schemes in a formal way, we take advantage of DEVS discrete-event modelling tools, which also allow us to develop a detailed simulation platform for our multi-agent system. The simulation experiments obtained on a detailed model of a manufacturing system derived from the literature confirm the effectiveness of the proposed approach.     

A methodology for controlling dispersion in food production and distribution

After a number of food safety crises, the design and implementation of traceability systems became an important tool for managing safety risks in the food industry. In the literature, numerous studies deal with traceability from the viewpoint of information system and technology development. However, traceability and its implications for food safety receive less attention in literature on production and distribution planning. From the viewpoint of operations management, an efficient management of food safety risks requires the consideration of the amounts of potentially recalled products, affected regions/customers, and logistics efforts connected to solving the safety problem. In this paper we are developing a production and distribution planning model for food supply chains to address these issues. We also present heuristics for solving the resulting mixed-integer linear programming model and demonstrate the effectiveness of the developed methodology in a numerical investigation.     

A Gated Radiometer for Plasma Afterglow Study

In order to monitor the electron temperature during plasma afterglow experiments, a gated microwave radiometer has been developed. The radiometer differs from the usual Dicke type of radiometer in the input switching scheme and in the fact that a good time resolution is required. The radiometer to be described has a time resolution of one microsecond and a temperature sensitivity of about ten degrees Kelvin when measuring temperatures near room temperature. The response time when used with a repetitive afterglow is 20 seconds. Measurements of electron temperature in a decaying nitrogen plasma have been made duirng the initial 300 microseconds of the afterglow.     

Reliability modeling for multistage systems subject to competing failure processes

In this paper, a novel multistage reliability model is provided as systems are often divided into many stages according to system degradation characteristics. Multistage hard failure (caused by random shock) process (MHFP) and multistage soft failure (caused by random shock and continuous degradation) process (MSFP) are introduced to describe the competing failure processes, where either the MSFP or MHFP would break down the system. The shock processes impact the system in three ways: (1) fatal load shocks cause hard failure immediately in the hard failure process; (2) time shocks cause a hard failure threshold changing; (3) damage load shocks cause degradation level increasing in the soft failure process. In this paper, a density function dispersion method is carried out to address the multistage reliability model, and the effectiveness of the proposed models is demonstrated by reliability analysis with the one-stage model. Finally, the multistage model is applied to a case study, the degradation process is divided into three stages, and the hard failure threshold can be transmitted twice. The proposed model can be applied in other multistage situations, and the calculation method can satisfy the accuracy requirements.     

Design of an integrated quality assurance strategy in production systems

High-quality of products is a critical issue for manufacturers to maintain their competitiveness in global markets. For this reason, more attention has been paid by operations managers and academics to the design of quality assurance strategies, acceptance sampling plans and inspection allocation problems. In the last decades, international research has studied and introduced several models and approaches to investigate these issues. The purpose of this paper is to provide a new methodology for designing and selecting correct integrated quality assurance strategies, defining cost models for acceptance policies and inspection station configurations. Generally, high-quality of items is guaranteed by avoiding defects, mainly caused by non-conforming components, resulting from instantaneous and standard infant mortality. Thus, an optimal acceptance policy is defined in order to reduce the instantaneous infant mortality defects. A closed-form equation has been introduced to determine easily and quickly the optimal percentage of checked items. Furthermore, a more convenient inspection station configuration is determined in order to minimise the expected total cost, composed of testing, inspection and penalty cost elements. The innovative concept of defect rate as an inspection time variable dependent has been introduced. The impact of different economic and survival parameters on designing inspection policies is also investigated. Finally, a real-life case study demonstrates the applicability of this methodology in real production systems and several considerations are reported about the future research, that the authors will carry out.