FINANCIAL PERFORMANCE ANALYSIS AS A BASED FOR FORMULATING A STRATEGIC PLAN FOR BUSINESS UNIT DEVELOPMENT

A study of all aspects of management needs the attention of the management. Financial Management with Financial Performance Analysis summarises the results of the implementation of various company policies in a certain period. It should be an essential management element. This study aimed to examine the determination of business strategies in the context of developing business units based on the results of financial performance analysis. The analysis period in this writing was the period 2012-2019. The analytical technique used in this research was descriptive quantitative that utilized several financial ratios to formulate business unit development strategies that referred to the Five Forces of Michael Porter and SWOT analysis. Based on the calculation result of several financial ratio analyzes, it can be concluded that the financial performance of PD Pantja Karya experienced good results at the beginning of the analysis period, namely 2012 to 2015 or 2016. In the period after 2014-1017, PD Pantja Karya’s financial performance tends to be bad. Using the Five Forces of Michael Porter analysis and SWOT analysis, it can be concluded that PD Pantja Karya continued the timber business unit to be carried out by implementing a stability strategy supported by several business management policies. Shipping and land transportation business units should implement a Development Strategy by focusing on operational efficiency

Knowledge Identity (KI): A New Approach to Integrating Knowledge Management into Enterprise Systems

Despite the extensive studies about KM over the past four decades, the discipline still lacks a clear and practically comprehensive understanding of how KM can be integrated into enterprise systems. To a high degree, the issue is associated with the ambiguous assumptions taken by organizations about knowledge. Many of the assumptions of information systems theories about knowledge require revision, particularly how knowledge is managed. Conceptualizing knowledge as processed data and information has led contemporary design and implementation of enterprise systems to fail to capture the complexity of knowledge. In this article, we critically examine these views. We argue that the answer to the question as to how and to what extent enterprise systems can support KM, depends on the assumptions that organizations take towards the nature and sources of knowledge. To address this question, we introduce the concept of Knowledge Identity (KI) and a model of Enterprise Knowledge Integration

Concurrent optimization of process parameters and product design variables for near net shape manufacturing processes

This paper presents a new systematic approach to the optimization of both design and manufacturing variables across a multi-step production process. The approach assumes a generic manufacturing process in which an initial Near Net Shape (NNS) process is followed by a limited number of finishing operations. In this context the optimisation problem becomes a multi-variable problem in which the aim is to optimize by minimizing cost (or time) and improving technological performances (e.g. turning force). To enable such computation a methodology, named Conditional Design Optimization (CoDeO) is proposed which allows the modelling and simultaneous optimization of process parameters and product design (geometric variables), using single or multi-criteria optimization strategies. After investigation of CoDeO’s requirements, evolutionary algorithms, in particular Genetic Algorithms, are identified as the most suitable for overall NNS manufacturing chain optimization The CoDeO methodology is tested using an industrial case study that details a process chain composed of casting and machining processes. For the specific case study presented the optimized process resulted in cost savings of 22% (corresponding to equivalent machining time savings) and a 10% component weight reduction

A system dynamics archetype to mitigate rework effects in engineer-to-order supply chains

There are established archetypes that demonstrate the dynamic properties of make-to-order/stock and assemble-to-order production planning and inventory control systems and their impact on total on-costs, allowing for performance benchmarks to be established. However, the dynamic properties of engineer-to-order (ETO) production system, where products are designed and made to a specific customer order, are not well understood. Time and cost-overrun, poor capacity planning and high rates of rework are difficulties faced by ETO managers and, for now, solutions for these problems are still lacking. Therefore, this paper develops an ETO production model which merges a service orientated design subsystem with a working-unit-orientated production subsystem to establish an order book-controlled ETO system. The developed model realises automatic capacity control to maintain the expected lead time and order book. At the same time, we also conduct transfer function and stability analysis on this holistic ETO model to investigate the system’s dynamic properties using Control Theory and System Dynamics. This paper’s contributions could be summarised from four perspectives. 1. It provides an automatic capacity-controlled archetype for practice benchmarking and demonstrating the advantage of a whole system level order book controller. 2. The order book proportional controller, at a whole system level rather than just in the local subsystems, can offset the rework’s negative impact, while achieving target order book and service times. 3. The dynamic analysis provides transfer functions, demonstrating the dynamic relationship between demand (input) with order book and lead time (outputs). 4. The derived critical condition for system stability provides guidelines for system managers to prevent the system becoming unstable. The limitation of this paper is that we assume the rework could only happen in the production system and could be rectified in the production system. However, in practice, rework could happen and be detected everywhere. Further research could relax this assumption and explore the dynamics of these scenarios

DEVELOPING A SYSTEMATIC APPROACH TO DESIGNING A DISCRETE EVENT CONTROL SYSTEM

The study reported in this thesis was aimed at laying a foundation for automating the design process of the discrete event control (DEC) system with the PLC (programmable logic controller) platform. The study had three objectives (in brief): (1) developing a model for technical specification of design requirements of DEC, (2) developing a systematic design process model for DEC, and (3) developing a framework for knowledge repository, in which the knowledge of systematic design of a DEC is stored. The research activity was carried out to achieve the three objectives. First, the current model of the technical specification of design requirements for a functional product called General Design Process Model (GDPM) was revised to the model for a DEC. Second, the general design process model for functional products, such as the open-ended synthesis from a customer’s voice of needs of a DEC to a technical specification of the need, decomposition of functions along with the control functions (both feedback and feedforward), and open-ended synthesis of devices along with their DECs, was combined with the specific design process model for DEC, such as generation of state equation, and generation of the software ladder logic diagram (or generic PLC code). Third, the type of knowledge to support each design step was identified and classified, and the structure of the knowledge was outlined. Last, a case study of designing a DEC for medical ventilator was conducted along with the simulation of the design to validate the efficacy of the design process model and knowledge repository. The research activities lead to the general conclusion that the objectives of this study can be achieved, suggesting that a computer system be feasibly built to conduct design of a DEC in future. The main contribution of the study lies in the field of design automation, including (1) the finding that the entire design process has two parts: open-ended part (first part) and close-ended part (second part), and (2) the demonstration of the feasibility of automating the design process for a DEC, which will have positive impact to designing a DEC more effectively and efficiently

DESIGN FOR A SUSTAINABLE E-COMMERCE SYSTEM -- INCORPORATING HUMAN FACTORS INTO DISTRIBUTION OF MEDICAL MATERIALS AND FAST-MOVING CUSTOMER GOODS IN INVENTORY CONTROL

The rise of e-commerce has revolutionized the way we shop with significant benefits in terms of convenience and accessibility. However, the most crucial operational management responsibilities required in an ecommerce supply chain business focusing on the distribution of medical materials and fast-moving consumer goods, are procurement, inventory control, order processing, logistics and last mile distribution. A typical ecommerce business faces problems like careless data entry from employees, returns and customer complaints, customer acquisition and retention, high labor cost and high operational cost. These lead to an increase in late delivery of orders to customer and often resulted to customer orders returned, loss of sales, customers dissatisfaction, and low profit. This thesis investigated an ecommerce business that distributed fast moving consumer goods (FMCG) and medical materials (MM) to their online customers. This research discusses the impact of HF such as job skill, job satisfaction, job rotation, and job fatigue, on workers' job performance in an ecommerce operation system that focuses on distribution of MM and fast-moving consumer goods. First, surveys were created with the intention of identifying the HF mentioned and quantifying their influence on the system work performance. The data were examined for validity, reliability, and correlation using statistical analysis techniques. The study hypotheses were as follows: (1) There is no significant impact of (HF), including job skills, job satisfaction, job rotation, and job fatigue, on job performance within the modern B2B e-commerce model of companies ABC and XYZ. (2) There is no significant impact of (HF) on the levels of job satisfaction, job fatigue, and job rotation among warehouse workers within the modern B2B e-commerce model of companies ABC and XYZ. (3) The combined influence of job skills, job satisfaction, job rotation, and job fatigue does not significantly impact the determination of job performance among workers in the B2B e-commerce of companies ABC and XYZ. To test these hypotheses, an experiment was created and carried out. The findings demonstrated an inconsequential significance between job skills, job satisfaction, job rotation, and job fatigue on job performance of the warehouse system. When making decisions in a real-world industrial context, these findings are anticipated to improve an ecommerce operation. The significant contributions of this thesis are summarized. First, this thesis work has increased the present understanding of HF and their significance in e-commerce operation, specifically in relation to the distribution of FMCG and MM, which will help the management of any ecommerce business make decisions in the fields of operations and supply chain management. Second, in starting an ecommerce business, this work has also shown that HF should be considered while investing in e-commerce business in terms of organizational goals and profit making

A Step Toward Improving Healthcare Information Integration & Decision Support: Ontology, Sustainability and Resilience

The healthcare industry is a complex system with numerous stakeholders, including patients, providers, insurers, and government agencies. To improve healthcare quality and population well-being, there is a growing need to leverage data and IT (Information Technology) to support better decision-making. Healthcare information systems (HIS) are developed to store, process, and disseminate healthcare data. One of the main challenges with HIS is effectively managing the large amounts of data to support decision-making. This requires integrating data from disparate sources, such as electronic health records, clinical trials, and research databases. Ontology is one approach to address this challenge. However, understanding ontology in the healthcare domain is complex and difficult. Another challenge is to use HIS on scheduling and resource allocation in a sustainable and resilient way that meets multiple conflicting objectives. This is especially important in times of crisis when demand for resources may be high, and supply may be limited. This research thesis aims to explore ontology theory and develop a methodology for constructing HIS that can effectively support better decision-making in terms of scheduling and resource allocation while considering system resiliency and social sustainability. The objectives of the thesis are: (1) studying the theory of ontology in healthcare data and developing a deep model for constructing HIS; (2) advancing our understanding of healthcare system resiliency and social sustainability; (3) developing a methodology for scheduling with multi-objectives; and (4) developing a methodology for resource allocation with multi-objectives. The following conclusions can be drawn from the research results: (1) A data model for rich semantics and easy data integration can be created with a clearer definition of the scope and applicability of ontology; (2) A healthcare system's resilience and sustainability can be significantly increased by the suggested design principles; (3) Through careful consideration of both efficiency and patients' experiences and a novel optimization algorithm, a scheduling problem can be made more patient-accessible; (4) A systematic approach to evaluating efficiency, sustainability, and resilience enables the simultaneous optimization of all three criteria at the system design stage, leading to more efficient distributions of resources and locations for healthcare facilities. The contributions of the thesis can be summarized as follows. Scientifically, this thesis work has expanded our knowledge of ontology and data modelling, as well as our comprehension of the healthcare system's resilience and sustainability. Technologically or methodologically, the work has advanced the state of knowledge for system modelling and decision-making. Overall, this thesis examines the characteristics of healthcare systems from a system viewpoint. Three ideas in this thesis—the ontology-based data modelling approach, multi-objective optimization models, and the algorithms for solving the models—can be adapted and used to affect different aspects of disparate systems