Multi-variate time-series for time constraint adherence prediction in complex job shops

One of the most complex and agile production environments is semiconductor manufacturing, especially wafer fabrication, as products require more than several hundred operations and remain in Work-In-Progress for months leading to complex job shops. Additionally, an increasingly competitive market environment, i.e. owing to Moore’s law, forces semiconductor companies to focus on operational excellence, resiliency and, hence, leads to product quality as a decisive factor. Product-specific time constraints comprising two or more, not necessarily consecutive, operations ensure product quality at an operational level and, thus, are an industry-specific challenge. Time constraint adherence is of utmost importance, since violations typically lead to scrapping entire lots and a deteriorating yield. Dispatching decisions that determine time constraint adherence are as a state of the art performed manually, which is stressful and error-prone. Therefore, this article presents a data-driven approach combining multi-variate time-series with centralized information to predict time constraint adherence probability in wafer fabrication to facilitate dispatching. Real-world data is analyzed and different statistical and machine learning models are evaluated

COBACABANA (control of balance by card based navigation):an alternative to kanban in the pure flow shop?

Kanban systems are widely applied in practice as they represent a simple yet effective means of controlling production. But they suffer from a lack of load balancing capabilities, which hinders their application even to pure flow shops if there is variability. In response, this study focuses on COBACABANA (Control of Balance by Card Based Navigation), a card-based production control approach based on the Workload Control concept that was recently introduced in the literature. COBACABANA was developed for high-variety job shop contexts, but we argue it can also provide an important control alternative to kanban systems in pure flow shops. We first show that, in the pure flow shop, the control loop structure of COBACABANA resembles that of a kanban system when the flow of jobs is controlled. But a distinct difference is COBACABANA׳s unique focus on load balancing. Using simulation, we then demonstrate the potential of COBACABANA to improve performance in a pure flow shop with high demand and processing time variability. Results show that a fixed gateway station – inherent to a pure flow shop – presents a structural constraint that makes COBACABANA׳s original starvation avoidance mechanism, which injects work to a starving station, dysfunctional. An alternative is prioritizing jobs with short processing times at upstream stations to ensure quick replenishment takes place at downstream stations threatened by starvation. This has important implications not only for COBACABANA but for priority dispatching. Although card-based systems are typically combined with first-come-first-served dispatching, our results suggest this may be inappropriate in flow shops with processing time variability

Stochastic flow shop scheduling model for the Panama Canal

The Panama Canal can be modeled as a stochastic flexible flow shop for the purpose of scheduling. A metaheuristic stochastic optimization method (Nested Partition) was used to determine if current scheduling practices could be improved by reducing the makespan for vessel traffic. Results indicate that classifying the vessels according to the time that they spend transiting the canal and using some rules and metaheuristic technique for parallel flow shop improves the makespan. The schedules produced by this method show distinct patterns as described by the sequence of vessel types

Job shop scheduling under dynamic and stochastic manufacturing environment

Ankara : Department of Industrial Engineering and the Institute of Engineering and Sciences of Bilkent Univ., 1995.Thesis (Master's) -- Bilkent University, 1995.Includes bibliographical references.In practice, manufacturing systems operate under dynamic and stochastic environment where unexpected events (or interruptions) occur continuously in the shop. Most of the scheduling literature deals with the schedule generation problem which is only one aspect of the scheduling decisions. The reactive scheduling and control aspect has scarcely been addressed. This study investigates the effects of the stochastic events on the s\'stem performance and develops alternative reactive scheduling methods. In this thesis, we also study the single-pass and multi-pass scheduling heuristics in dynamic and stochastic job shop scheduling environment. We propose a simulation-based scheduling system for the multi-pass heuristics. Finally, we analyze the interactions among the operational strategies (i.e, lookahead window, scheduling period, method used for scheduling), the system conditions, and the unexpected events such as machine breakdowns and processing time variations.Kutanoğlu, ErhanM.S

Card-based production control:a review of the control mechanisms underpinning Kanban, ConWIP, POLCA and COBACABANA systems

Since the emergence of Kanban, there has been much research into card-based control systems. This has included attempts to improve Kanban and/or develop alternative systems, particularly ConWIP (i.e. Constant Work-In-Process), POLCA (i.e. Paired-cell Overlapping Loops of Cards with Authorisation) and COBACABANA (i.e. Control of Balance by Card-Based Navigation). Yet, to date, no unifying review of the mechanisms underpinning these systems has been presented. As a consequence, managers are not provided with sufficient support for choosing an appropriate system for their shop; and researchers lack a clear picture of how the mechanisms compare, leading to several misconceptions. This paper reviews the control mechanisms underpinning the Kanban, ConWIP, POLCA and COBACABANA systems. By comparing the ‘control mechanism’ (i.e. the loop structure and card properties) and ‘contextual factors’ (i.e. routing variability, processing time variability, and whether stations are decoupled by inventory or the flow of jobs is controlled), we provide managers with guidance on which system to choose. For research, we show for example that most criticisms put forward against Kanban systems, e.g. to justify the development of ConWIP, POLCA or COBACABANA, only apply to work-in-process Kanban systems and not to production Kanban systems. Future research directions for each control system are outlined

Experimental investigation of iterative simulation-based scheduling in a dynamic and stochastic job shop

A vital component of modern manufacturing systems is the scheduling and control system, which determines companies' overall performance in their respective supply chains. This paper studies iterative simulation-based scheduling mechanisms for manufacturing systems that operate in dynamic and stochastic environments. Also assessed are the issues involved when these mechanisms are used to make higher-level scheduling decisions, such as dispatching rule selection, instead of generation of a full schedule. A typical simulation-based system is outlined and tested under various experimental conditions. Examined are the effects of stochastic events such as machine breakdowns and processing time variations on the system performance, and the effectiveness of the simulation-based approach from the control point of view is evaluated. Finally, different levels of two important factors (look-ahead window and scheduling period) are compared for the iterative approach. Computational results show that, although simulation-based scheduling proves effective when these parameters are properly set, the overall performance diminishes due to the dynamic and stochastic nature of the system, which degrades the multi-pass improvement capability of the simulation runs. Experimental results also support the initial expectation in that frequent updates to the higher-level schedule may not be necessary when these decisions are naturally "adaptive" to the unexpected system changes

An integrated approach for remanufacturing job shop scheduling with routing alternatives.

Remanufacturing is a practice of growing importance due to increasing environmental awareness and regulations. However, the stochastic natures inherent in the remanufacturing processes complicate its scheduling. This paper undertakes the challenge and presents a remanufacturing job shop scheduling approach by integrating alternative routing assignment and machine resource dispatching. A colored timed Petri net is introduced to model the dynamics of remanufacturing process, such as various process routings, uncertain operation times for cores, and machine resource conflicts. With the color attributes in Petri nets, two types of decision points, recovery routing selection and resource dispatching, are introduced and linked with places in CTPN model. With time attributes in Petri nets, the temporal aspect of recovery operations for cores as well as the evolution dynamics in cores\u27 operational stages is mathematically analyzed. A hybrid meta-heuristic algorithm embedded scheduling strategy over CTPN is proposed to search for the optimal recovery routings for worn cores and their recovery operation sequences on workstations, in minimizing the total production cost. The approach is demonstrated through the remanufacturing of used machine tool and its effectiveness is compared against another two cases: baseline case with fixed recovery process routings and case 2 using standard SA/MST

EVALUATION OF SETUP ECONOMIES IN CELLULAR MANUFACTURING

This dissertation addresses two research questions relating to the role of setups in discrete parts manufacturing. The first research topic uses a carefully designed simulation study to investigate the role of setup economies in the factory-wide conversion of functional layouts (job shops) to cellular manufacturing. The model-based literature shows a wide dispersion in the relative performance of cellular manufacturing systems as compared to the original job-shop configurations, even when the key performance measure is flow time and the assessment tool used is simulation. Using a standardized framework for comparison, we show how this dispersion can be reduced and consistent results can be obtained as to when the conversion of the job shop is advantageous. The proposed framework standardizes the parameters and operational rules to permit meaningful comparison across different manufacturing environments, while retaining differences in part mix and demand characteristics. We apply this framework to a test bed of six problems extracted from the literature and use the results to assess the effect of two key factors: setup reduction and the overall shop load (demand placed on the available capacity). We also show that the use of transfer batches constitutes an independent improvement lever for reducing flow time across all data sets. Finally, we utilize the same simulation study framework to investigate the benefits of partial transformation, where only a portion of the job shop is converted to cells to work alongside a remainder shop. The second research question examines the role of dispatching rules in the reduction of setups. We use queueing models to investigate the extent of setup reduction analytically. We single out the Alternating Priority (AP) rule since it is designed to minimize the incidence of setups for a two-class system. We investigate the extent of setup reductions by comparing AP with the First-Come-First-Served (FCFS) rule. New results are obtained analytically for the case of zero setup times and extended to the case of non-zero setup time through computational studies

Effect of information delays on the performance of flexible manufacturing systems : an empirical investigation

http://deepblue.lib.umich.edu/bitstream/2027.42/35477/2/b2073365.0001.001.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/35477/1/b2073365.0001.001.txthttp://deepblue.lib.umich.edu/bitstream/2027.42/35477/6/wp02-002.pd

Centralised vs. decentralised control decision in card-based control systems:comparing kanban systems and COBACABANA

Kanban systems are simple yet effective means of controlling production. Production control is decentralised or exercised locally on the shop floor, i.e. a downstream station signals to an upstream station that an item is needed. If items are always the same and known, then demands can be satisfied instantaneously from stock; but if items differ and are unknown, demands must first be propagated backwards from station to station before being satisfied. The former is defined as an inventory control problem and the latter as an order control problem. Handling the order control problem via kanban involves a decentralised card acquisition process (during which information is propagated from station to station) that is separated from the actual production process. COBACABANA (control of balance by card-based navigation), an alternative card-based solution, shares kanban’s control structure but centralises the card acquisition process. Evaluating the two systems therefore provides a unique opportunity to compare decentralised and centralised control. Using simulation, we demonstrate that it is specifically the centralised card acquisition process that allows COBACABANA to balance the workload across resources and thus to outperform kanban in an order control problem. This has major implications for research and practice