Ergonomics Analysis Integrated Into The Process Planning For Manufacturing System At Ford

Abstract

The occupation of ergonomics in the manufacturing workplace and on the Assembly line flow is a unfavourable issues which needs to be addressed in order to the avoid workplace injuries and prevent work action which leads to long term medical problem for the workers. In 1990 the Ford motor company established or implemented the application in which they handle artificial intelligence Technology for inspection of potential ergonomics issues have to do before the work instructions into the Assembly plant the manufacture of motor vehicles is a complicated and high powered problem and the worth related to be workplace irrecoverable productiveness because of bad ergonomics design will be very sententious. We added to different ergonomics analysis system that has been integrated into the process planning for manufacturing system at Ford and global study and process allocation system. GSPAS became the Global depot for standardized engineering process and data for assembling all for vehicles including part tools and standard labour time. The another complicated benefit of GSPAS as is the use of control language which is also known as the standard language. Standard language is a Ford specific restricted exercise of English that is used to describe the vehicle assembly process at Ford Motor company this language is used as the input to the artificial intelligence component of the Global study process allocation system. Potential ergonomics written in standard language which was read by the artificial intelligence system and used to generate work assembly instructions which was introduced in North America. The work report here allow how we assemble upon preceding outcome with artificial intelligence to elaborate the technology into the new region of Economics analysis.

Introduction

At the 6th annual applied economics conference held in Dallas TX in March of 2003,The Institute of Industrial engineers IIE awarded the ERGO CUP training education to Ford motor company. We have been beneficially implement Artificial Intelligence and another intelligence techniques with Ford vehicles operation since 1990. In this application it is mostly with the planning and configuring of vehicle assembly process planning. In this process sheets written in free form text which caused major problems because of ambiguity and lack of consistency. The use of control language has disqualify almost all ambiguity in process sheet instruction and has created as standard format for writing process sheet across the Corporation which create work allocations for the plant fruit and to estimate level time accurately. This system is also known as the Direct labour management system that is the system is based on Knowledge that occupied semantic network knowledge representation schemes DLMS using techniques from control Language Processing instructions logics and classified based reasoning to generate detailed plan through assembly instruction from high level processes destruction this system is also provide us detailed estimate of the labor content that is required from this process description. This involved in the progress and preservation of large-scale knowledge bases on ontology has made us to apply this technology to other complicated areas within manufacturing. Techniques such as machine revolution and evolutionary computation were integrated into DLMS to support knowledge base investigation and occupied DLMS to ford assembly plants then that don’t using English as their main language .

The process sheet is the initial vehicle for giving vehicle assembly information from the centrality engineering functions to the assembly plants. It contains specific information about work instructions and describes the parts and tools required for the build process. The work that is Reported to build the vehicle according to the process sheet instructions is then be allocated among the usable person. Work places requires a easiest means of finding the labour time that is needed for any specific task. The DLMS system using these instructions and determining a list of detailed actions which are required to implement these instructions at the assembly plant level.

These work instructions, known as “allocatable elements”, are associated with MODAPTS (Modular Arrangement of Predetermined Time Standards) codes which are used to calculate the time required to perform these actions. MODAPTS codes are widely used as a means of measuring the body movements that are required to perform a physical action and have been accepted as a valid work measurement system. For example, the MODAPTS code for moving a small objective only a hand is M2; utilizing the arm gives a code of M3. The MODAPTS codes are then combined to describe an entire sequence of actions. MODAPTS codes are then converted into an equivalent time required to perform that action. Subsequently the ergonomics engineers would manually inspect the process sheets for doubt ergonomic issue. Since there may be 1000 or more process sheets for every single type of vehicle that Ford manufactures, this manual type of inspection was very labor intensive and time-consuming. An ergonomics engineer would spend upwards of two weeks in manually inspecting each process build instruction for a vehicle. In an effort to streamline this process we developed a

System that would automate the inspection of process sheets for ergonomics deploys. This work resulted in the development of an artificial intelligence system for ergonomic analysis within GSPAS that checks for two types of potential ergonomics issues: "red" and "warning". Process sheets that are flagged as "red" will not be sent to the assembly plants until those errors are corrected. Process sheets that are flagged with "warning" messages are released to the assembly plants; however, the ergonomic specialists have the opportunity to check and approve these issues through the use of a system that was built specifically for this application. The Ergonomics system was developed and application production in April of 2002. Since that time, more than 1100 process sheets with ergonomics problems were interrupted by the AI system from going into production at the assembly plants. This has already resulted in a savings of over $17,000,000 in injury cost avoidance as the high risk processes never made it to the plant floor. These calculations are based on the type of injuries prevented and the direct cost associated per injury for each type of ergonomic problem.

In this article, we discuss how artificial intelligence technology was used to prevent potential ergonomic issues at our assembly plants with elaborate benefits in reducing workplace injuries and time lost by workers. Part 2 discusses the problem of ergonomics analysis for manufacturing. Part 3 provides a detailed description of the ergonomics analysis that is being performed by the system. We discuss the application of AI technology in Part 4. An analysis of the benefits provided by our system is given in part 5. The application deployment and maintenance is discussed in part 6.

Problem Description

The proactive Ergonomics group within Vehicle operations at Ford Motor Company is responsible for the launch of all future vehicles with ergonomically correct assembly. This team starts working as early as four years before the vehicle is launched to develop standardized ergonomic strategies for vehicle assembly and design. This work includes checking the process build instructions For every vehicle for potential ergonomic issues. A complete ergonomics analysis would include the Following:

• Find the assembly work instruction to investigate what type of physical action is being described: (ex. LOAD, POSITION, OBTAIN) and what the preservation of the work is.
• Find the assembly work instruction to investigate what object is being manipulated (ex. BRACKET ASSEMBLY INNER)
• Find the assembly work instruction in Standard Language to investigate what parts and tools are needed for this operation.
• Find the associated parts and investigate what part Is being used and the weight of that part. Find the associated tools and investigate the properties of the tool to see how it impacts the operation.

The manufacturing build instructions are written in Standard Language, which is a "controlled language" that was developed specifically at Ford. Standard Language has been in use at Ford since the early 1990s and is used worldwide by Ford engineers to describe the assembly process for virtually all vehicle programs. A controlled language defines a set of explicit restrictions and Constraints on the grammar, lexicon and style of the document being produced. The major aim of these constraints is to reduce the ambiguity, redundancy, size and complexity of the language that is being written. A specific type of verb, known as a Standard Language verb, was used as the basis of Standard Language usage. Each standard Language verb (we currently have 134) was carefully defined to represent a specific action and was used as the main driver for a Standard Language element or sentence. Only one Standard Language verb is valid per element and the resulting actions from a process instruction are based on the interaction between the verb, the object, Any modifiers and the tools and parts that are used in the element. The ergonomics engineers identified those verbs that are associated with potential risk factors (force, frequency and posture). Thresholds were assigned to each trigger verb to assess the level of risk based in part on the force and frequency associated with the element.

Process Sheet Written in Standard Language

TITLE: ASSEMBLE IMMERSION HEATER TO ENGINE 10 OBTAIN ENGINE BLOCK HEATER ASSEMBLY FROM STOCK 20 LOOSEN HEATER ASSEMBLY TURNSCREW USING POWER TOOL 30 APPLY GREASE TO RUBBER O-RING AND CORE OPENING 40 INSERT HEATER ASSEMBLY INTO RIGHT REAR CORE PLUG HOSE 50 ALIGN SCREW HEAD TO TOP OF HEATER TOOL 20 1 P AAPTCA TSEQ RT ANGLE NUTRUNNER TOOL 30 1 C COMM TSEQ GREASE BRUSH PART 10 1 01 7499 01 S-011201 B ENGINE BLK HEATER ASSY figure 1: Sample GSPAS Process Sheet In this example, the ergonomics engineer would need to determine if this process sheet has any potential ergonomics concerns. In element 10 the engineer determined that the OBTAIN operation requires an operator to get a "engine block heater assembly" part from the part bin and walk back to his station. This could potentially cause a concern if the part weighed above a certain threshold; therefore the engineer would need to look up the weight of the part. If the part weighed more than a certain threshold (in this case 35 pounds) the engineer would also need to check if a "lift assist" type tool was assigned to this element. If there were no lift assist tool assigned, the engineer would flag this job as having an ergonomic concern due to the excessive weight that the operator would need to carry. As stated previously, this type of manual analysis was unfeasible due to the sheer volume of data that needed to be analysed. Potential ergonomics problems that were not flagged before they reached the assembly plant floor would need to be fixed at the plant and this would entail additional delay and expense. Therefore, our challenge in this project was to develop an automated method that could flag potential ergonomics concerns before they reached the assembly plant.

Ergonomics A Uses of artificial intelligence Technology

The economics investigation tool is used at fault makes use of the following artificial Technologies description logics natural language processing and rule based processing The height of our artificial intelligence system is knowledge base that occupy are semantic network model to represent all of the automobile assembly planning information the use of First 70 network as a part of knowledge representation system is also known as the description logics description logic implementation known as the Classic has been successfully used to develop telecommunication equipment configurator

Application use and payoff

The ergonomics determination tool has been occupied at Port for approximately 2 years. The Smash up of this system can be sum up as follows

• The industrialization of the ergonomics red Converting interrupted over 1100 process sheets with potential ergonomic trouble from reaching the assembling plant
• The industrialization of the ergonomics warning processing reduce the work conditions of the ergonomics engineers by 20%.
• The engineer that would be wrote the process sheet became aware of Economics occupation and started writing their process sheets to address this occupation before they were flagged by the system
• Ergonomics is a necessary occupation to both ford and the UAW.

They give us the quantifiable benefits of the system that include the cost saving over 17th million dollars in term of avoiding injuries was associated with the red triggers as well as reduce the number of warning triggers that premier Rebel to been manually inspected by 20%. The scope of the artificial intelligence for the ergonomics engineer is that can make their job easier and improve the efficiency of the plant. The benefit of the system both quantifiable and indirect,were primeval higher than the development cost and system has been a very successful mechanical application of artificial intelligence.