Scheduling research in multiple resource constrained job shops: a review and critique

Over the past several years, a number of survey, classification, and review articles have focused on scheduling research in machine [only] constrained job shops. Barring the work of Treleven (1989), there is no reported research that presents a detailed review of the issues related to scheduling and sequencing in job shops with multiple resource constraints. In his article, Treleven reviewed the research in job shops constrained by machines and labour. Job shops are not only constrained by machines and labour, but by auxiliary resources (in the form of tooling. etc.) as well. This paper extends the work of Treleven by reviewing the literature on scheduling in job shops constrained by more than one resource and comparing the scheduling research in auxiliary resource-constrained job shops with that of labour-constrained job shops. In addition, this article raises some issues for future scheduling research in multiple resource-constrained job shops

Clips: a capacity and lead time integrated procedure for scheduling.

We propose a general procedure to address real life job shop scheduling problems. The shop typically produces a variety of products, each with its own arrival stream, its own route through the shop and a given customer due date. The procedure first determines the manufacturing lot sizes for each product. The objective is to minimize the expected lead time and therefore we model the production environment as a queueing network. Given these lead times, release dates are set dynamically. This in turn creates a time window for every manufacturing order in which the various operations have to be sequenced. The sequencing logic is based on a Extended Shifting Bottleneck Procedure. These three major decisions are next incorporated into a four phase hierarchical operational implementation scheme. A small numerical example is used to illustrate the methodology. The final objective however is to develop a procedure that is useful for large, real life shops. We therefore report on a real life application.Model; Models; Applications; Product; Scheduling;

Reinforcement learning for an intelligent and autonomous production control of complex job-shops under time constraints

Reinforcement learning (RL) offers promising opportunities to handle the ever-increasing complexity in managing modern production systems. We apply a Q-learning algorithm in combination with a process-based discrete-event simulation in order to train a self-learning, intelligent, and autonomous agent for the decision problem of order dispatching in a complex job shop with strict time constraints. For the first time, we combine RL in production control with strict time constraints. The simulation represents the characteristics of complex job shops typically found in semiconductor manufacturing. A real-world use case from a wafer fab is addressed with a developed and implemented framework. The performance of an RL approach and benchmark heuristics are compared. It is shown that RL can be successfully applied to manage order dispatching in a complex environment including time constraints. An RL-agent with a gain function rewarding the selection of the least critical order with respect to time-constraints beats heuristic rules strictly by picking the most critical lot first. Hence, this work demonstrates that a self-learning agent can successfully manage time constraints with the agent performing better than the traditional benchmark, a time-constraint heuristic combining due date deviations and a classical first-in-first-out approach

Shop-floor scheduling as a competitive advantage:A study on the relevance of cyber-physical systems in different manufacturing contexts

The aim of this paper is to analyse the relevance of cyber-physical systems (CPS) in different manufacturing contexts and to study whether CPS could provide companies with competitive advantage by carrying out a better scheduling task. This paper is developed under the umbrella of contingency theory which states that certain technologies and practices are not universally applicable or relevant in every context; thus, only certain companies will benefit from using particular technologies or practices. The conclusion of this paper, developed through deductive reasoning and supported by preliminary simulation experiments and statistical tests, is that factories with an uncertain and demanding market environment as well as a complex production process could benefit the most from implementing a CPS at shop-floor level since a cyber-physical shop-floor will provide all the capabilities needed to carry out the complex scheduling task associated with this type of context. On the other hand, an increase in scheduling performance due to a CPS implementation in factories with simple production flows and stable demand could not be substantial enough to overcome the high cost of installing a fully operational CPS

Job Loss and Infrastructure Job Creation During the Recession

[Excerpt] After the long economic expansion that characterized much of the current decade, the nation entered its eleventh postwar recession in December 2007. The unemployment rate rose from 5.0% in that month to 6.7% in November 2008, the latest data released to date by the U.S. Bureau of Labor Statistics (BLS). A majority of those unemployed in November—some 6 out of 10 million people—had been laid off by their employers. In November 2008 alone, employment at nonfarm businesses fell by 533,000, marking the biggest one-month drop recorded by the BLS Current Employment Statistics program since December 1974. The announcement by the Business Cycle Dating Committee in November 2008 that a recession had begun, which preceded by one week the monthly BLS Employment Situation release containing employment and unemployment data for November, intensified congressional interest in passage of legislation aimed at encouraging creation of new jobs and warding off the further loss of jobs. In the 110th Congress, the Senate did not act on legislation (H.R. 7110) the House passed in September 2008, which contained among other things spending on infrastructure (public works) projects to promote employment in the troubled construction industry and in industries that supply it with goods and services (e.g., concrete and steel manufacturing). To mitigate all but one recession since the 1960s, Congress has chosen to increase federal expenditures on infrastructure. This means of job creation has not been without its critics, however, chiefly because of how long it typically takes for public works projects to start up. (See CRS Report 92-939, Countercyclical Job Creation Programs, by Linda Levine, for more information.) This would seem to be less of an issue if the recession is a long one and if Congress passes the legislation while the recession is still taking place. Members of Congress have spoken of having ready for the president’s signature shortly after his inauguration a second economic stimulus bill that would include provisions to create and maintain jobs in the construction industry and in other infrastructure-dependent industries. A more expansive definition of public works than was used in the past is under consideration; one which includes so-called green jobs. Although no consensus definition currently exists, they appear to include jobs in the renewable energy industries (e.g., wind, solar), jobs retrofitting buildings to be more energy efficient, and jobs expanding mass transit systems. The report first examines trends in employment and job loss since the start of the latest recession. It next focuses on job creation estimates associated with increased spending on infrastructure, placing a heavy emphasis on explaining the limitations and caveats associated with the input-output methodology that often is utilized to develop the estimates. The report will be updated after the 111th Congress convenes to reflect legislation that includes “direct job creation” provisions, i.e., economic stimulus bills having the government raise demand for goods and services through increased federal spending for the purpose of creating and preserving jobs. It will not discuss stimulus measures that give consumers more money in the hope they will spend rather than save it and that provide income support such as extension of unemployment benefits. (Information on these forms of fiscal stimulus can be found in CRS Report RL34349, Economic Slowdown: Issues and Policies, by Jane G. Gravelle et al.

Scheduling of a computer integrated manufacturing system: a simulation study

Purpose: The purpose of this paper is to study the effect of selected scheduling dispatching rules on the performance of an actual CIM system using different performance measures and to compare the results with the literature. Design/methodology/approach: To achieve this objective, a computer simulation model of the existing CIM system is developed to test the performance of different scheduling rules with respect to mean flow time, machine efficiency and total run time as performance measures. Findings: Results suggest that the system performs much better considering the machine efficiency when the initial number of parts released is maximum and the buffer size is minimum. Furthermore, considering the average flow time, the system performs much better when the selected dispatching rule is either Earliest Due Date (EDD) or Shortest Process Time (SPT) with buffer size of five and the initial number of parts released of eight. Research limitations/implications: In this research, some limitations are: a limited number of factors and levels were considered for the experiment set-up; however the flexibility of the model allows experimenting with additional factors and levels. In the simulation experiments of this research, three scheduling dispatching rules (First In/First Out (FIFO), EDD, SPT) were used. In future research, the effect of other dispatching rules on the system performance can be compared. Some assumptions can be relaxed in future work. Practical implications: This research helps to identify the potential effect of a selected number of dispatching rules and two other factors, the number of buffers and initial number of parts released, on the performance of the existing CIM systems with different part types where the machines are the major resource constraints. Originality/value: This research is among the few to study the effect of the dispatching rules on the performance of the CIM systems with use of terminating simulation analysis. This is also significant given the nature of the CIM systems that are mostly used to produce different parts in varying quantities and thus do not produce parts on a continuing basis. This research is amongst the first to study the combined effect of dispatching rule and the buffer size in the CIM systems where the job arrivals are predetermined and depend on the completion of the existing parts in the system. A description of how buffer size and initial part release is related to the performance of the CIM system under study for the studied priority dispatching rule is also provided.Peer Reviewe

Cycle Time Analysis For Photolithography Tools In Semiconductor Manufacturing Industry With Simulation Model : A Case Study [TR940. S618 2008 f rb].

Perkembangan industri semikonduktor dalam bidang fabrikasi biasanya melibatkan kos pelaburan yang tinggi terutamanya dalam alatan photolithography. The industry of semiconductor wafer fabrication (“fab”) has invested a huge amount of capital on the manufacturing equipments particular in photolithograph

An Extension to the Tactical Planning Model for a Job Shop: Continuous-Time Control

We develop an extension to the tactical planning model (TPM) for a job shop by the third author. The TPM is a discrete-time model in which all transitions occur at the start of each time period. The time period must be defined appropriately in order for the model to be meaningful. Each period must be short enough so that a job is unlikely to travel through more than one station in one period. At the same time, the time period needs to be long enough to justify the assumptions of continuous workflow and Markovian job movements. We build an extension to the TPM that overcomes this restriction of period sizing by permitting production control over shorter time intervals. We achieve this by deriving a continuous-time linear control rule for a single station. We then determine the first two moments of the production level and queue length for the workstation.Singapore-MIT Alliance (SMA

Evolutionary methods for the design of dispatching rules for complex and dynamic scheduling problems

Three methods, based on Evolutionary Algorithms (EAs), to support and automate the design of dispatching rules for complex and dynamic scheduling problems are proposed in this thesis. The first method employs an EA to search for problem instances on which a given dispatching rule performs badly. These instances can then be analysed to reveal weaknesses of the tested rule, thereby providing guidelines for the design of a better rule. The other two methods are hyper-heuristics, which employ an EA directly to generate effective dispatching rules. In particular, one hyper-heuristic is based on a specific type of EA, called Genetic Programming (GP), and generates a single rule from basic job and machine attributes, while the other generates a set of work centre-specific rules by selecting a (potentially) different rule for each work centre from a number of existing rules. Each of the three methods is applied to some complex and dynamic scheduling problem(s), and the resulting dispatching rules are tested against benchmark rules from the literature. In each case, the benchmark rules are shown to be outperformed by a rule (set) that results from the application of the respective method, which demonstrates the effectiveness of the proposed methods