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Minimising makespan aims to achieve high utilisation of equipment and resources by getting all jobs out quickly. This is an important scheduling criterion, especially for automated systems, because of the high investment cost. The problem, however, becomes complex when many parts and machines are involved. This is because different parts may require different numbers of operations, and there are many possible schedules. For small problems, a mathematical programming model for minimising makespan is formulated. For large problems, a sequencing algorithm based on decomposition and pairwise comparison is proposed. The idea of “total overlapping time” in the sequencing algorithm is introduced to determine the solution of each sub‐schedule. It maximises the number of jobs working at different machines at the same time, while satisfying the parts’ operation precedence and machine constraints. The differences between this method and the traditional graphical method are discussed. The sequencing algorithm significantly reduces the number of schedules for consideration and hence, the computational power required.

Minimizing penalty cost is one of the major objectives in FMS decision making when job‐due dates cannot be met. The study focuses on minimization of penalty cost when neither increase in system capacity nor diversification of jobs to other plants or production lines is possible. A mathematical programming model combining both part type selection and scheduling decision making is proposed for small problems. For large problems, a simple control parameter is identified. Seven despatching rules are applied in conjunction with the control parameter and their differences in performance are reported. Not only proves that performance can be improved by a filtration process applied before despatching rules are applied, but also finds that there is no significant difference in performance between different despatching rules after the appropriate filtration process is applied. The effectiveness of the proposed control parameter is further illustrated by comparing the results with a continuous flow model.

Job sequencing is an important stage in any hierarchical production control model, especially when a real‐time dispatching rule is not employed. The problems become complicated when constraints, such as different parts requiring different operation processes at different machines and with different production priorities, are taken into consideration in the development of sequencing models. This paper first describes a mathematical programming model developed for small flexible manufacturing systems (FMS) makespan minimization sequencing problems. For large problems, a heuristic decomposition‐based algorithm is proposed. The algorithm is based on the proposed concept of track generation and track identification. Each part type may require a different number of operation processes at different machines. A numerical example is used to illustrate the use of the algorithm.

Research on knowledge creation within eSports learning is scarce. This study extends the understanding of competition-oriented collaborative learning in eSports by examining the relationship between the dynamics of knowledge creation modes and the continuum of the motivational profile, along with the moderating effects of mutualistic co-presence therein.

Participants were recruited from the community of massively multiplayer online gamers (MMOGs). Through a quantitative survey, their motivations (i.e. self-extrinsic, self-intrinsic, peer-extrinsic and peer-intrinsic motivations), knowledge creation involvements (i.e. internalization, externalization, combination and socialization) and perception of mutualistic benefit of self and peers were captured for hypothesis testing.

Significant and positive direct relationships were observed between four motivations and four knowledge creation modes. The mutualistic co-presence positively moderated the positive relationship between the self-extrinsic, peer-extrinsic and peer-intrinsic motivations and socialization. When mutualistic self-benefit were outweighed, peer-extrinsic motivated gamers became less likely to perform internalization, whereas self-extrinsic and peer-extrinsic motivated gamers were less likely to perform combination.

This study is among the first to rationalize the relationship between motivational profile and the dynamics of knowledge creation in eSports learning. The conceptualization of the new construct – mutualistic co-presence – using the ecological concept of symbiosis is uncommon in prior literature. The findings also demonstrate that the four modes of knowledge creation in eSports learning are continuous and interwoven; they can be initiated at any point and do not necessarily occur in a specific sequence.