Identifying the Key Attributes in an Unlabeled Event Log for Automated Process Discovery

Process mining discovers and analyzes a process model from historical event logs. The prior art methods use the key attributes of case-id, activity, and timestamp hidden in an event log as clues to discover a process model. However, a user needs to specify them manually, and this can be an exhaustive task. In this paper, we propose a two-stage key attribute identification method to avoid such a manual investigation, and thus this is a step toward fully automated process discovery. One of the challenging tasks is how to avoid exhaustive computation due to combinatorial explosion. For this, we narrow down candidates for each key attribute by using supervised machine learning in the first stage and identify the best combination of the key attributes by discovering process models and evaluating them in the second stage. Our computational complexity can be reduced from $\mathcal{O}(N^3)$ to $\mathcal{O}(k^3)$ where $N$ and $k$ are the numbers of columns and candidates we keep in the first stage, respectively, and usually $k$ is much smaller than $N$. We evaluated our method with 14 open datasets and showed that our method could identify the key attributes even with $k = 2$ for about 20 seconds for many datasets.Comment: IEEE Transactions on Services Computing (Early Access version

Learning to Search for Job Shop Scheduling via Deep Reinforcement Learning

Recent studies in using deep reinforcement learning (DRL) to solve Job-shop scheduling problems (JSSP) focus on construction heuristics. However, their performance is still far from optimality, mainly because the underlying graph representation scheme is unsuitable for modeling partial solutions at each construction step. This paper proposes a novel DRL-based method to learn improvement heuristics for JSSP, where graph representation is employed to encode complete solutions. We design a Graph Neural Network based representation scheme, consisting of two modules to effectively capture the information of dynamic topology and different types of nodes in graphs encountered during the improvement process. To speed up solution evaluation during improvement, we design a novel message-passing mechanism that can evaluate multiple solutions simultaneously. Extensive experiments on classic benchmarks show that the improvement policy learned by our method outperforms state-of-the-art DRL-based methods by a large margin

Retail Precinct Management: A Case of Commercial Decentralization in Singapore

AbstractThis paper reviews the logistics challenges of a decentralization strategy in Singapore. The main purpose of an urban decentralization, where the commercial hubs and retail clusters are distributed in several regional centers is to relieve congestion from the city center and to move business closer to home. However, this approach can also create congestion in regional centers due to the rapid flow of public, private and freight vehicles in and out of regional centers. This paper identifies three major challenges and proposes Retail Precinct Management (RPM) which consists of four inter-related components to overcome these challenges

How digitalisation can enable industrial symbiosis practices : a case study

Industrial Symbiosis (IS) encourages a collaborative approach aiming at recovering, reprocessing and reusing non-labour resources and it is a promising solution for mitigating the rising cost of non-labour resource. Introducing IS is a knowledge intensive process and researchers have developed various information and communication (ICT) tools to support the process. However, the use of these tools in the actual industrial practice has not been adequately investigated yet. This study investigates the role that ICT tools play in facilitating the process of creating IS through a case study of International Synergies – the company which facilitated the world’s first national-level IS programme (i.e. NISP UK). Results suggest that the role of digitalisation can increase practitioners’ productivity mainly through data analytics

Computer integrated selection and sequencing of modular orienting devices for vibratory bowl feeders

The role of part orientation in automatic assembly is the key to automatic assembly. Often, vibratory bowls have been used to successfully align parts into the correct orientation for subsequent assembly operations. However, the present trend towards flexible, small batch production has rendered expensive and impractical, dedicated part feeders meant for a specific part or a limited range of parts from a part family. Also, traditionally, the design and tooling of the vibratory bowls are confined to the compiled and causal knowledge of a small group of skilled individuals.Master of Engineering (MPE