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Ibukun Onifade

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About Ibukun Onifade

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Profile Information

  • Name
    Ibukunoluwa Onifade
  • Company
    Dufil Prima Foods PLC, Ogun State, Nigeria
  • Designation
    Lean Six Sigma Facilitator

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  1. Overall equipment effectiveness is the most acceptable measure for the assessing the performance of any operation. There are 3 major components of OEE; 1. Availability – Downtimes happen in the course of operations mostly when least expected. Downtimes could be as a result of equipment failure, material shortage, shift changeover, product changeover, etc. These downtimes result in a direct loss of output for their entire duration. Availability is calculated by subtracting the downtime from the total available time, then expressing it as a percentage of the total available time.
  2. CONWIP (Constant Work In Progress) is a method of implementing pull in an operating system. CONWIP is a combination of pull and push systems. The entrance of an item into the system is based on pull, but its movement through the processes towards the end is based on push. The inventory in a CONWIP system is controlled only at the end of the line, there is always a fixed amount of finished goods inventory that can be kept at anytime. This system is maintained by the use of cards, a completed product frees up a card which will be attached to the new entrant into the system. In CONWIP, nothing is
  3. Planning poker is a consensus-based, gamified technique used often for estimating the effort required to accomplish a certain goal or relative size of development goals in software development. In planning poker, members of the group make estimates by playing numbered cards face-down to the table, instead of speaking them aloud. When all have played their cards, the cards are revealed simultaneously, and the estimates are then discussed. By revealing the figures at the same time, the group can avoid the cognitive bias of anchoring, where the first number spoken aloud influences the estimate o
  4. Filter bubble as a phrase was first used by Eli Pariser in his 2011 New York Times bestselling book, The Filter Bubble: What the internet is hiding from you. It is a term used to describe the personalization of individual online experience by the use of computer algorithms. These algorithms customize what an online user sees based on his online history. For example, if a user has been reading articles that support a particular viewpoint, this algorithm will filter his feed such that he will be seeing mostly articles that support the viewpoint he holds. The user find himself in a kind of world
  5. Paralysis by analysis – data driven decision making is becoming increasingly popular in organizations. But to what limit should we depend on data analysis to make decisions? Scenarios abound where the main objective of data analysis end up being defeated because of nothing else but excessive analysis. What should ideally bring clarity becomes the cause of confusion. Typical situations of paralysis by analysis are; a. Dialogue of the deaf – To get approval for certain actions, much data analysis is done to justify such decisions higher management. Unfortunately in many cases, the hig
  6. Instruction creep is a common problem especially in large organizations. Standard operating procedures are usually modified frequently once any lapse is perceived by people responsible for maintaining order in the process. This continuous addition often leads to a complex guideline that most workers find tedious to read through or implement completely. In fact, most workers do not read their usually voluminous SOPs not to talk of following the contents. Many guidelines have been rendered ineffective because of this anomaly. The following steps can be taken to avoid instruction creep; 1.
  7. Reporting bias happens when a researcher’s report is influenced by the nature and significance of the results. This sometimes defeat the objective of research. 1. Multiple publication bias: This happens when the results of a study are published multiple times most especially when they are favourable. Data is also sometimes duplicated within the same study. Studies should always be subjected to rigorous reviews to avoid this kind of bias. 2. Location bias: This happens when pulling results from different databases. Studies stored on some databases are already influenced by
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