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Much research has been reported on the possibilities of using various heuristic priority rules to sequence batches through a job shop. The SPT (Shortest Priority Time) heuristic, or modifications to it, has been proved useful in many studies. This paper reports on the results obtained when simulating the work flow through a real machine shop. The simulation model has been used to test the effect on well known priority rules of releasing batches into the shop in order of decreasing expected throughput time. The important effect of this “phased release” of batches was to increase the percentage of batches delivered in finished parts stores on time, particularly in the case where priority rules were in use which might otherwise have resulted in poor delivery. This has important repercussions for management because it implies that by “phased” release of batches in the manner discussed, a large proportion of batches will be delivered on time whatever priority rule is in operation in the shop.

Motivated by recent research indicating that the operational performance of an enterprise can be enhanced by building a supporting data-driven environment in which to operate, this paper presents a simulation framework that enables an examination of the effects of applying smart manufacturing principles to conventional production systems, intending to transition to digital platforms.

To investigate the extent to which conventional production systems can be transformed into novel data-driven environments, the well-known constant work-in-process (CONWIP) production systems and considered production sequencing assignments in flowshops were studied. As a result, a novel data-driven priority heuristic, Net-CONWIP was designed and studied, based on the ability to collect real-time information about customer demand and work-in-process inventory, which was applied as part of a distributed and decentralised production sequencing analysis. Application of heuristics like the Net-CONWIP is only possible through the ability to collect and use real-time data offered by a data-driven system. A four-stage application framework to assist practitioners in applying the proposed model was created.

To assess the robustness of the Net-CONWIP heuristic under the simultaneous effects of different levels of demand, its different levels of variability and the presence of bottlenecks, the performance of Net-CONWIP with conventional CONWIP systems that use first come, first served priority rule was compared. The results show that the Net-CONWIP priority rule significantly reduced customer wait time in all cases relative to FCFS.

Previous research suggests there is considerable value in creating data-driven environments. This study provides a simulation framework that guides the construction of a digital transformation environment. The suggested framework facilitates the inclusion and analysis of relevant smart manufacturing principles in production systems and enables the design and testing of new heuristics that employ real-time data to improve operational performance. An approach that can guide the structuring of data-driven environments in production systems is currently lacking. This paper bridges this gap by proposing a framework to facilitate the design of digital transformation activities, explore their impact on production systems and improve their operational performance.

Several prior studies have investigated the strategy of concurrently deploying different priority rules at different processing stages of a manufacturing system. The purpose of this paper is to investigate the advantage of using such a strategy over that of using priority rules in their pure forms.

Three priority rules were combined in all possible ways in a simulated, three‐stage, flow‐dominated manufacturing system. The performances of these combinations, along with three other simple priority rules in their pure forms, were compared using both mean and variability in waiting, earliness, tardiness, and total costs under two shop load levels and several tardiness to earliness cost ratios.

The results indicate that the combinations between SI^X and shortest processing time (SPT) rules perform well in reducing both mean and variability of waiting cost but do poorly on tardiness cost. On the other hand, the due date rule in its pure form or in conjunction with SI^X or SPT is effective in reducing both mean and variability of both earliness and tardiness costs. While tardiness cost appears to dominate the total cost data, the shop load level registered little impact on the performance of the combination schemes.

The results of the paper have useful practical implications for textile and ceramic industries. However, the conclusions are limited to the cost structure used, although a wide range of cost ratios is included.

The paper offers insights into whether throughput and due date‐related costs can be reduced by using a job sequencing strategy that simultaneously deploys different priority rules at different processing stages of a manufacturing environment.

Constructing an effective production control policy is the most important issue in wafer fabrication factories. Most of researches focus on the input regulations of wafer fabrication. Although many of these policies have been proven to be effective for wafer fabrication manufacturing, in practical, there is a need to help operators decide which lots should be pulled in the right time and to develop a systematic way to alleviate the long queues at the bottleneck workstation. The purpose of this study is to construct a photolithography workstation dispatching rule (PADR). This dispatching rule considers several characteristics of wafer fabrication and influential factors. Then utilize the weights and threshold values to design a hierarchical priority rule. A simulation model is also constructed to demonstrate the effect of the PADR dispatching rule. The PADR performs better in throughput, yield rate, and mean cycle time than FIFO (First‐In‐First‐Out) and SPT (Shortest Process Time).

Discusses the twofold purpose of this study, first to introduce a number of measures devised to be used in comparing and evaluating two schedules for the same project, second to present and evaluate a heuristic procedure developed in this research for solving the resource constrained project scheduling problem. Posits that the new procedure is based on the notion that a project can be partitioned into a number of sections and there is no obligation to use a single policy all the way through all the sections of project. Shows that this research is also an attempt to bridge the gap between the theory and practice by eliminating the question of which priority rule to use for which project. Develops a new model showing that selecting from a number of priority rules is not required and, using the measures of performance introduced, decides on a suitable schedule from the schedules produced under varied assumptions is shown to be much easier. Concludes with suggestions for further research.

Deals with the dynamic scheduling problems and solutions of job shop comprising six work centres and n components. Concerns the behaviour of the system, with the arrival of urgent orders and normal orders. In a typical manufacturing system, urgent orders are scheduled for processing based on their urgency and given priority over normal orders. Describes an analysis of urgent order processing on the basis of non pre‐emptive priority and pre‐emptive resume priority over normal orders. Enumerates manufacturing system performances which had been analysed for the two most popular scheduling rules – first in first out (FIFO) and shortest processing time (SPT) – through a system simulation program. Concludes by asserting that the simulation program can be used to schedule the manufacturing system dynamically by choosing the appropriate scheduling rule to measure optimal system performance leading to higher productivity.

Steam turbine final assembly is a dynamic process, in which various interference events occur frequently. Currently, data transmission relies on oral presentation, while scheduling depends on the manual experience of managers. This mode has low information transmission efficiency and is difficult to timely respond to emergencies. Besides, it is difficult to consider various factors when manually adjusting the plan, which reduces assembly efficiency. The purpose of this paper is to propose a knowledge-based real-time scheduling system under cyber-physical system (CPS) environment which can improve the assembly efficiency of steam turbines.

First, an Internet of Things based CPS framework is proposed to achieve real-time monitoring of turbine assembly and improve the efficiency of information transmission. Second, a knowledge-based real-time scheduling system consisting of three modules is designed to replace manual experience for steam turbine assembly scheduling.

Experiments show that the scheduling results of the knowledge-based scheduling system outperform heuristic algorithms based on priority rules. Compared with manual scheduling, the delay time is reduced by 43.9%.

A knowledge-based real-time scheduling system under CPS environment is proposed to improve the assembly efficiency of steam turbines. This paper provides a reference paradigm for the application of the knowledge-based system and CPS in the assembly control of labor-intensive engineering-to-order products.

Reports development and simulation of real‐time dispatching procedures, for flexible manufacturing cells (FMCs) in constant production circumstances, where a fixed set of part types is processed continuously while maintaining constant ratios between quantities needed of each part type. Five different procedures were tested: the first based on a simple rule, called the largest relative advantage (LRA) rule; two procedures linear programming based (named FMLPP and ALPP); a pull‐type procedure; and the last based on SPT rule. As expected, one of the linear programming based procedures achieved the best results. However, the much simpler LRA based procedure produced similar results, especially in the presence of machine failures. It was shown that, for high processing flexibility, good performance may be achieved by a dispatching procedure using the cell processing flexibility. In contrast to this, in low processing flexibility situations, there is no significant difference between the various scheduling procedures.

The purpose of this paper is to find out whether, which and how international corporations use their codes of conduct to guide employees double‐bound by contradicting cultural norms.

The paper draws on integrative social contracts theory to content‐analyse the codes of conduct of the “Fortune Global 500” and the “UNCTAD 100”.

The vast majority of international corporations' codes either does not acknowledge contradictions between equally binding norms, or lacks priority rules for employees to resolve them. Nonetheless, several codes of conduct describe how norms might contradict, give clear priority to one set of norms (local or corporate) and provide specific examples to employees of when and how to apply a priority rule.

The paper identifies the 33 codes of conduct which can serve as best practices for international corporations' employee and corporate communication.

Contradictions between cultural norms are unacknowledged or unresolved in communication practice and little explored in corporate communication research. This paper assesses the scope of this caveat in communication practice and offers solutions in the form of an existing normative theory and of newly identified best practices.

Scheduling of production in a wire rope factory is complicated by several features: (a) the simultaneous requirement for two types of limited resource, machines and bobbins; (b) multi‐stage production with normally two or three stranding and one or two closing operations; (c) queuing at the closing machines; the typical job splits into sub‐batches when passing from the stranding to the closing operation; these sub‐batches usually queue at the closing operations which, being faster than stranding operations, generally receive work from several queues; (d) alternative choices in the selection of machines and bobbin sizes for any given stranding or closing operation; (e) the presence of random elements in the timing of machine breakdowns and repairs. In this case study factory in a developing country, the existing control of production flows was ad hoc rather than according to a specified method. The management needed to know whether a scientific scheduling approach could significantly improve the low utilisation of machines. As a first attempt a strategy was synthesised based on well‐known concepts from the theory of scheduling in static and dynamic environments, taking into consideration certain effects of the complicating factors mentioned above. Simulation revealed that a significant improvement was possible.