Multiobjective Advanced Planning and Scheduling using iterative Genetic Algorithm

Models and P4R asset description for digital twin-based advanced planning and scheduling using cyber-physical integration for resilient production operation

Advanced Process Control Modeling from an Advanced Planning and Scheduling Perspective

Intense global competition and declining profit have caused most thin film transistor liquid crystal display manufacturers to increase their competitiveness by improving productivity and reducing cycle times. An advanced planning and scheduling (APS) system was developed with Microsoft Visual Basic for Application to automatically generate production schedules for a color filter fab with multiple lines. This system can assign orders to production lines, plan order release time, and balance the equipment loading. Both forward scheduling and backward scheduling were used in APS. Experimental results indicated that APS can significantly reduce manual scheduling time while maintaining the quality of scheduling results. Compared to manual operations, it can save more than 87 % of scheduling time and the quickness is especially important when rescheduling is needed due to production uncertainties such as equipment breakdown or material shortage. Production controllers can use this APS to generate initial schedule and make adjustment based on experience.

In this paper, the system integration of an Advanced Planning and Scheduling (APS) system with Enterprise Resource Planning (ERP) and Manufacturing Execution System (MES) for a Semiconductor Backend Assembly environment is described. The company is one of the worldwide market leaders in semiconductor packaging technology. SIMTech was responsible for the implementation of the Planning & Scheduling functions through its APS application which is called Gintic Scheduling System (GSS). GSS system has been integrated with the other two key manufacturing software systems, namely ERP and MES, with the CIM framework. This paper emphasizes the system integration between the GSS and the customer's existing ERP and MES systems. The paper starts with a broader overview of the APS, ERP and MES systems with the focus on the linkage of APS with ERP and APS with MES. It then introduces the brief background information of the implementation and the integration methodology. Detailed work of the integration is laid out in the fond of integration model structure and illustrated by the system integration mechanism. Various data types that need to be integrated are also elaborated. Further discussions continue with the practical implementation issue like the required frequency of data integration and also the two approaches of data transfer. Finally the paper shares the experiences and lessons the team has learned through the implementation process and concludes the essence of the system integration work.

Web services are widely discussed and proposed to address enterprise integration within company or cross-organizations due to its language and operating system independency and support of loosely coupled integration. This paper presents an architecture for APS (advanced planning and scheduling) system by describing its messaging mode) and service model, attempting to solve integration issues among APS, MES, ERP and other manufacturing systems that could not be handled properly using current approaches. In addition, a prototype of enterprise integration constructed for a semiconductor packaging company using Java Web services enabling technologies will demonstrate the advantages and benefits of the solution

Within the framework of Industry 4.0, the transition from stand-alone systems to an interconnected digital enterprise plays a crucial role. Increasing demands for flexibility, quality, and shorter product development cycles drive the adoption of advanced digital solutions such as product data management (PDM) systems, manufacturing execution systems (MES), advanced planning and scheduling (APS) tools, and the digital twin (DT) concept. At the same time, digitalisation trends (e.g., Smart Factory) reveal critical weaknesses of manufacturing companies, with insufficient planning and scheduling capabilities being one of the most common issues. While medium- and long-term planning is typically handled within ERP systems, operational scheduling is often still managed through inflexible spreadsheet-based solutions. APS systems are therefore gaining importance as effective tools with relatively fast return on investment, although their deployment requires alignment between ERP and MES layers as well as a thorough understanding of business and production processes. The combined implementation of PDM, APS, MES, and DT enhances decision-making, enables rapid adaptability to change, and supports the development of learning organisations. The article focuses on key principles and technologies of digital transformation with emphasis on data integration using selected tools.

Most manufacturing small and medium sized companies (SMEs) deal with constraint issues on a daily basis in terms of missing materials or lack of production capacity. Only a few of these companies have implemented Advanced Planning and Scheduling (APS) systems, which enables constraint based planning, as existing APS systems are aimed at the high-end market (e.g. Manugistics and 12) or part of large ERP suites (e.g. Oracle, SAP or BaaN). This means that the infeasible plans are sent to the shop floor, or that the planner has dealt with the constraint issues manually. Both situations are unacceptable in an agile manufacturing company.

Adaptive Job-shop Control Based on Permanent Order Sequencing

The activities of preparing and issuing Forensic Science Services reports are a public service of great importance for society and for the executive and judicial branches. However, notably, it has difficulties in meeting due dates, causing damage to all involved and generating additional costs for governments. In practice, it is observed that knowledge in the area of operations management is not used to determine the allocations of Forensic Science services at Criminalistics Technical Sections. Therefore, the objective of this research is to develop and apply knowledge related to the operations scheduling of Forensic Science reports. To fulfill the objective, the case study research method was applied in the Regional Technical Section of Criminalistics (STRC) of Três Corações - Minas Gerais in Brazil. Real data from that Forensic Unity carried out in the past were implemented in an APS (Advanced Planning and Scheduling) software and new allocations, based on the software's internal algorithms, were carried out. The results of allocations from the software have been compared with the previous results. The comparisons show that scheduling from the software's algorithms can bring better results.

An intelligent agent for ERP's data structure analysis based on ANSI/ISA-95 standard

There is nothing permanent except change. The only constant is change. Many engineering changes must be communicated to a broad range of stakeholders. The process is often labor intensive, paper laden, and error prone. Product data management (PDM) system and configuration management theory are the most popular system and theory for handling engineering changes today. In practice, when utilizing a product data management system, a planned effectivity must be filled in each engineering change request (ECR) during analyzing and evaluating phase of an engineering change. A change effectivity decision may be required to identify all of the required actions, the responsibility, and the timing from detail design phase to production phase in the life cycle of the product. This paper presents a specific product configuration, which is called engineering change decision bill of materials (ECD-BOM). The procedure for generating such a product configuration from product data management system is also provided. Import states of such product configuration into an advanced planning and scheduling (APS) system, planned effectivity of approved changed configuration items are then computed.

Purpose – Studies conducted on advanced planning and scheduling (APS) systems have found problems in the marginal or negative returns from APS systems when they are implemented in manufacturing planning and control processes. The purpose of this study is to examine what problems exist in the onward and upward phase of the APS system implementation and how the individual, technical and organizational (ITO) dimensions in the implementation phases influence the problems in the onward and upward phase. Design/methodology/approach – Three different manufacturing companies using a supply chain planning module to support their tactical manufacturing planning processes were chosen and their APS system implementation phases were studied. Interviews with the project members and the end-users, and on-site visits, were conducted. Internal company data and presentations were collected and analyzed according to four implementation phases and the ITO dimensions. Findings – Three types of problems were identified in the onward and upward phase: process-related problems concerning difficulties to move forward; dependency on a consultancy firm; and too much time spent in the system. System-related problems include the usage of parallel systems and inadequate usage of the appropriate potential of the APS system. Plan-related problems regard an incorrect production plan. Different relationships between the ITO dimensions in the implementation process and the problem type were proposed. Practical implications – The relationships identified in this paper are of important knowledge for companies who are implementing, or are in the process of implementing, APS systems. Originality/value – There has been little written about the implementation issues of APS systems. The practical use of APS systems in the tactical planning is also relatively low. It is not known what problems to expect and how the ITO dimensions influence the problems during implementation. The findings this paper discusses fill some of these gaps.

Diversified and complicated manufacturing sites make optimal scheduling of production lines difficult. Under current manufacturing processes, it is almost impossible for schedulers to consider all the constraints of production processes. A strategy of simulation-based advanced planning and scheduling (APS) is employed to overcome difficulties that interfere with satisfactory on-time delivery and commitment to the current status. In simulation-based scheduling, key performance indices (KPIs) are important for selecting optimal dispatching rules in scheduling. In cases involving complex processes, in which the identification of appropriate KPIs is limited to selection among existing KPIs, KPIs should be chosen and modified carefully to optimize process management and to reflect all of the existing constraints of production. However, the existing methodologies for modifying KPIs are misplaced in complex manufacturing environments such as job-shop processes. We propose a new method to design and select appropriate KPIs that meet the characteristics of any given process, and verify with empirical analysis whether or not the KPIs meet requirements from experts of production lines.

Production planning and controls usually involve numerous business application systems, including manufacturing execution systems (MES), enterprise resource planning (ERP), advanced planning and scheduling (APS) and other information systems. Implementing each of these systems is a complex, costly and time-consuming project. Moreover, due to the fierce competition in the global market, mass customization has become the mainstream in the demand-driven environment which increases the difficulties in the integration of heterogeneous information systems. This research adopts a case study approach to examine the business application integration processes in the demand-driven environment and to identify potential solution in the project. Specifically, this study proposes a reference framework of integrated application systems for production planning and shop-floor control, and discusses several implications of such large-project implementation.

Complex electronic equipment final assembly workshops face challenges such as high coupling between information and physical systems, difficulty in integrating multi-source heterogeneous data, and frequent dynamic disturbances. These lead to severe information silos, lagging responses in dynamic scheduling, and low management efficiency. Based on Cyber-Physical System (CPS) theory, this paper proposes and constructs a digital workshop integrated application platform featuring a real-time data-driven collaborative scheduling framework integrating Digital Twin (DT) and Multi-Agent System (MAS). Firstly, a unified CPS framework integrating Manufacturing Operations Management (MOM), Supervisory Control and Data Acquisition (SCADA), Warehouse Management System (WMS), Visualization System (VDS), Advanced Planning and Scheduling (APS), and Digital Twin (DT) is established. Secondly, an ontology-based data encoding specification is designed to reduce interface coupling between systems. Furthermore, through the deep integration of DT and MAS, real-time dynamic response under high-frequency disturbances and closed-loop optimization of the assembly process are achieved. Application on a pulse assembly line for complex electronic equipment shows: assembly disturbance response time reduced by 50%, first-pass yield rate of final assembly increased to 99.32%, material distribution and plan matching degree exceeding 99%, average production waiting time reduced by over 30%, significantly enhancing workshop transparency and overall management and control efficiency.