A review of data visualization: opportunities in manufacturing sequence management.

Data visualization now benefits from developments in technologies that offer innovative ways of presenting complex data. Potentially these have widespread application in communicating the complex information domains typical of manufacturing sequence management environments for global enterprises. In this paper the authors review the visualization functionalities, techniques and applications reported in literature, map these to manufacturing sequence information presentation requirements and identify the opportunities available and likely development paths. Current leading-edge practice in dynamic updating and communication with suppliers is not being exploited in manufacturing sequence management; it could provide significant benefits to manufacturing business. In the context of global manufacturing operations and broad-based user communities with differing needs served by common data sets, tool functionality is generally ahead of user application

PlanningVis: A visual analytics approach to production planning in smart factories

Production planning in the manufacturing industry is crucial for fully utilizing factory resources (e.g., machines, raw materials and workers) and reducing costs. With the advent of industry 4.0, plenty of data recording the status of factory resources have been collected and further involved in production planning, which brings an unprecedented opportunity to understand, evaluate and adjust complex production plans through a data-driven approach. However, developing a systematic analytics approach for production planning is challenging due to the large volume of production data, the complex dependency between products, and unexpected changes in the market and the plant. Previous studies only provide summarized results and fail to show details for comparative analysis of production plans. Besides, the rapid adjustment to the plan in the case of an unanticipated incident is also not supported. In this paper, we propose PlanningVis, a visual analytics system to support the exploration and comparison of production plans with three levels of details: a plan overview presenting the overall difference between plans, a product view visualizing various properties of individual products, and a production detail view displaying the product dependency and the daily production details in related factories. By integrating an automatic planning algorithm with interactive visual explorations, PlanningVis can facilitate the efficient optimization of daily production planning as well as support a quick response to unanticipated incidents in manufacturing. Two case studies with real-world data and carefully designed interviews with domain experts demonstrate the effectiveness and usability of PlanningVis

Driving a lean transformation using a six sigma improvement process

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; in conjunction with the Leaders for Manufacturing Program at MIT, 2004.Includes bibliographical references (p. 73-74).Successive transformations within manufacturing have brought great efficiencies to producers and lower costs to consumers. With the advents of interchangeable parts between 1800 and 1850 in small arms manufacturing (Hounshell, 1984, pp. 3-4), mass production in the early 1900s in automobile manufacturing (Hounshell, 1984, pp. 9-10), and lean production in the early 1950s in automobile manufacturing (Womack, Jones, & Roos, 1990, p. 52), the state of manufacturing has continued to evolve. Each time, the visionaries that catalyzed the transformations were forced to overcome the inertia of the status quo. After convincing stakeholders of the need for change, these change agents: 1. Established a vision for the future 2. Committed resources to attain that vision 3. Studied the root causes for current methods 4. Proposed a new solution 5. Implemented the new solution 6. Quantified the results and sought future improvements. This basic process to implementing change is remarkably simple yet incredibly powerful. By explicitly emphasizing the need for root cause analysis, the process recognizes that improvements will be transient if the root causes of prior problems are not fully understood and resolved. When deploying a lean production system, an understanding of lean principles and tools is necessary but therefore not sufficient. Rather, implementing a lean production system should follow: 1. An analysis mapping the root causes of current production methods back to technical issues and the organization's strategic design, culture, and political landscape. Only by fixing the problems that led to the current production system can a lean transformation be sustained. 2. A detailed plan which achieves a transformation in both the organization(cont.) production system.by Satish Krishnan.S.M.M.B.A