Bullers, Nof, and Whinston’s (1980) study explored specific issues of concern in manufacturing systems planning and control. Their research focused on the problems relevant to automatic operations. According to the authors, they wanted to establish how artificial intelligence can be incorporated into the manufacturing environment to provide a solution to the possible challenges experienced. They based their argument on well-researched work elaborating their findings using different sets of data. They further explained the points using illustrative problems to indicate how glitches can be handled through a decision support system, especially when there is conflict occurrence. The researchers have cited several scholars who have contributed to different aspects such as computer information that is closely related to manufacturing and operations that aids managers in decision-making. The article summary will explore the significance of artificial intelligence in facilitating decision-making in manufacturing planning and control settings.
Based on Bullers et al. (1980) study, the research problem is the decision-making process in manufacturing planning and control that is complex and makes the management and control of manufacturing activities complicated. According to the authors, manufacturing environments are mainly controlled by shop-floor computers and other process controllers with predetermined system range functionality. Since the machines are operating in an interdependent manner, they require timely decisions at different levels of operations. From the view of writers, irrespective of the computer’s ability to process large information from the provided data, there is a need for human intervention to sift through the data to command them to execute some crucial actions. The inability makes them able to make proper planning and control decisions at the manufacturing level.
The problem addressed by the researchers is crucial to the technological world. In the current generation, most businesses are applying digital technology to enhance their business operations. Without a proper understanding of the shortfalls that the management may experience if they completely rely on the decision made by the process control computer, the planning activities may face dire challenges. The issue covered by the authors elaborates shows the need to have a deep understanding of how computers operate to increase their output efficiency. The problem allows me to explore more areas involving automatic machine system operations related to my project.
According to the work of Bullers et al. (1980), there are three main levels of activities involved in managerial decision-making in manufacturing planning and control. They include tactical manufacturing, production and inventory, and operational process of material flow. The authors argued that the manufacturing environment is dynamic and entails various factors that significantly influence all the levels that require decision-making. The article states different machine systems have been manufactured to enable managers to make constructive conclusions concerning the manufacturing activities they encounter.
The authors added that in settings where computers control the operations of different facilities automatically, supervisors face complicated roles, which is critical to the respective organization. This is because most of the systems are operating interdependently, thus requiring properly timed decisions in various stages of manufacturing. According to the researchers, the manufacturing environment is controlled by shop floor and process controllers. The systems are programmed in prior, thus making them incapable of adapting and processing planning decisions that contain unstructured data.
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Bullers et al. (1980) formulated a new approach that can enable managers to have productive decision support without relying on computer operators to execute actions for the system to process the available data. Based on the article, the authors stated that artificial intelligence technology is the ultimate solution to the problems associated with the inability of the system to provide effective planning and control. They continued to say that the technology will facilitate automatic manufacturing, thus increasing the productivity of the management.
The article states that having the technology will allow the transfer of human intelligence needed to make crucial operational decisions to the computer. This approach will ensure most of the judgments are made
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